R-universe search: black

kjhealy

gssrdoc:Document General Social Survey Variable

The General Social Survey (GSS) is a long-running, mostly annual survey of US households. It is administered by the National Opinion Research Center (NORC). This package contains the a tibble with information on the survey variables, together with every variable documented as an R help page. For more information on the GSS see \url{http://gss.norc.org}.

Maintained by Kieran Healy. Last updated 11 months ago.

120.3 match 2.28 score 38 scripts

schochastics

networkdata:Repository of Network Datasets

The package contains a large collection of network dataset with different context. This includes social networks, animal networks and movie networks. All datasets are in 'igraph' format.

Maintained by David Schoch. Last updated 12 months ago.

dataset network-analysis

33.4 match 143 stars 5.01 score 143 scripts

mlr-org

bbotk:Black-Box Optimization Toolkit

Features highly configurable search spaces via the 'paradox' package and optimizes every user-defined objective function. The package includes several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). bbotk is the base package of 'mlr3tuning', 'mlr3fselect' and 'miesmuschel'.

Maintained by Marc Becker. Last updated 3 months ago.

bbotk black-box-optimization data-science hyperparameter-optimization hyperparameter-tuning machine-learning mlr3 optimization

13.6 match 22 stars 9.87 score 166 scripts 14 dependents

modeloriented

DALEX:moDel Agnostic Language for Exploration and eXplanation

Any unverified black box model is the path to failure. Opaqueness leads to distrust. Distrust leads to ignoration. Ignoration leads to rejection. DALEX package xrays any model and helps to explore and explain its behaviour. Machine Learning (ML) models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance. But such black-box models usually lack direct interpretability. DALEX package contains various methods that help to understand the link between input variables and model output. Implemented methods help to explore the model on the level of a single instance as well as a level of the whole dataset. All model explainers are model agnostic and can be compared across different models. DALEX package is the cornerstone for 'DrWhy.AI' universe of packages for visual model exploration. Find more details in (Biecek 2018) <https://jmlr.org/papers/v19/18-416.html>.

Maintained by Przemyslaw Biecek. Last updated 1 months ago.

black-box dalex data-science explainable-ai explainable-artificial-intelligence explainable-ml explanations explanatory-model-analysis fairness iml interpretability interpretable-machine-learning machine-learning model-visualization predictive-modeling responsible-ai responsible-ml xai

8.3 match 1.4k stars 13.40 score 876 scripts 21 dependents

darwin-eu

CDMConnector:Connect to an OMOP Common Data Model

Provides tools for working with observational health data in the Observational Medical Outcomes Partnership (OMOP) Common Data Model format with a pipe friendly syntax. Common data model database table references are stored in a single compound object along with metadata.

Maintained by Adam Black. Last updated 18 days ago.

9.1 match 12 stars 11.39 score 502 scripts 12 dependents

murrayefford

secr:Spatially Explicit Capture-Recapture

Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.

Maintained by Murray Efford. Last updated 3 days ago.

cpp

9.0 match 3 stars 10.18 score 410 scripts 5 dependents

bioc

GreyListChIP:Grey Lists -- Mask Artefact Regions Based on ChIP Inputs

Identify regions of ChIP experiments with high signal in the input, that lead to spurious peaks during peak calling. Remove reads aligning to these regions prior to peak calling, for cleaner ChIP analysis.

Maintained by Matt Eldridge. Last updated 5 months ago.

chipseq alignment preprocessing differentialpeakcalling sequencing genomeannotation coverage

18.3 match 4.93 score 10 scripts 4 dependents

ahudde

greeks:Sensitivities of Prices of Financial Options and Implied Volatilities

Methods to calculate sensitivities of financial option prices for European, geometric and arithmetic Asian, and American options, with various payoff functions in the Black Scholes model, and in more general jump diffusion models. A shiny app to interactively plot the results is included. Furthermore, methods to compute implied volatilities are provided for a wide range of option types and custom payoff functions. Classical formulas are implemented for European options in the Black Scholes Model, as is presented in Hull, J. C. (2017), Options, Futures, and Other Derivatives. In the case of Asian options, Malliavin Monte Carlo Greeks are implemented, see Hudde, A. & Rüschendorf, L. (2023). European and Asian Greeks for exponential Lévy processes. <doi:10.1007/s11009-023-10014-5>. For American options, the Binomial Tree Method is implemented, as is presented in Hull, J. C. (2017).

Maintained by Anselm Hudde. Last updated 2 days ago.

asian-option greeks implied-volatility option cpp

14.6 match 7 stars 5.75 score 6 scripts

bgreenwell

pdp:Partial Dependence Plots

A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.

Maintained by Brandon M. Greenwell. Last updated 3 years ago.

black-box-model machine-learning partial-dependence-function partial-dependence-plot visualization

6.7 match 93 stars 11.72 score 1.1k scripts 8 dependents

omelnikov

QFRM:Pricing of Vanilla and Exotic Option Contracts

Option pricing (financial derivatives) techniques mainly following textbook 'Options, Futures and Other Derivatives', 9ed by John C.Hull, 2014. Prentice Hall. Implementations are via binomial tree option model (BOPM), Black-Scholes model, Monte Carlo simulations, etc. This package is a result of Quantitative Financial Risk Management course (STAT 449 and STAT 649) at Rice University, Houston, TX, USA, taught by Oleg Melnikov, statistics PhD student, as of Spring 2015.

Maintained by Oleg Melnikov. Last updated 10 years ago.

28.0 match 2 stars 2.67 score 47 scripts

enricoschumann

NMOF:Numerical Methods and Optimization in Finance

Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.

Maintained by Enrico Schumann. Last updated 30 days ago.

black-scholes differential-evolution genetic-algorithm grid-search heuristics implied-volatility local-search optimization particle-swarm-optimization simulated-annealing threshold-accepting

7.5 match 36 stars 9.56 score 101 scripts 4 dependents

mangothecat

BLCOP:Black-Litterman and Copula Opinion Pooling Frameworks

An implementation of the Black-Litterman Model and Attilio Meucci's copula opinion pooling framework as described in Meucci, Attilio (2005) <doi:10.2139/ssrn.848407>, Meucci, Attilio (2006) <doi:10.2139/ssrn.872577> and Meucci, Attilio (2008) <doi:10.2139/ssrn.1117574>.

Maintained by Joe Russell. Last updated 4 years ago.

12.8 match 6 stars 5.37 score 39 scripts

braverock

PortfolioAnalytics:Portfolio Analysis, Including Numerical Methods for Optimization of Portfolios

Portfolio optimization and analysis routines and graphics.

Maintained by Brian G. Peterson. Last updated 3 months ago.

6.0 match 81 stars 11.49 score 626 scripts 2 dependents

mlr-org

mlr3mbo:Flexible Bayesian Optimization

A modern and flexible approach to Bayesian Optimization / Model Based Optimization building on the 'bbotk' package. 'mlr3mbo' is a toolbox providing both ready-to-use optimization algorithms as well as their fundamental building blocks allowing for straightforward implementation of custom algorithms. Single- and multi-objective optimization is supported as well as mixed continuous, categorical and conditional search spaces. Moreover, using 'mlr3mbo' for hyperparameter optimization of machine learning models within the 'mlr3' ecosystem is straightforward via 'mlr3tuning'. Examples of ready-to-use optimization algorithms include Efficient Global Optimization by Jones et al. (1998) <doi:10.1023/A:1008306431147>, ParEGO by Knowles (2006) <doi:10.1109/TEVC.2005.851274> and SMS-EGO by Ponweiser et al. (2008) <doi:10.1007/978-3-540-87700-4_78>.

Maintained by Lennart Schneider. Last updated 13 days ago.

automl bayesian-optimization bbotk black-box-optimization gaussian-process hpo hyperparameter hyperparameter-optimization hyperparameter-tuning machine-learning mlr3 model-based-optimization optimization optimizer random-forest tuning

6.7 match 25 stars 8.57 score 120 scripts 3 dependents

jrvarma

jrvFinance:Basic Finance; NPV/IRR/Annuities/Bond-Pricing; Black Scholes

Implements the basic financial analysis functions similar to (but not identical to) what is available in most spreadsheet software. This includes finding the IRR and NPV of regularly spaced cash flows and annuities. Bond pricing and YTM calculations are included. In addition, Black Scholes option pricing and Greeks are also provided.

Maintained by Jayanth Varma. Last updated 3 years ago.

9.6 match 11 stars 5.90 score 48 scripts 1 dependents

pyfe

FER:Financial Engineering in R

R implementations of standard financial engineering codes; vanilla option pricing models such as Black-Scholes, Bachelier, CEV, and SABR.

Maintained by Jaehyuk Choi. Last updated 4 years ago.

bachelier black-scholes derivatives financial-engineering mathematical-finance option-pricing quantitative-finance

11.6 match 12 stars 4.76 score 12 scripts

r-lib

crayon:Colored Terminal Output

The crayon package is now superseded. Please use the 'cli' package for new projects. Colored terminal output on terminals that support 'ANSI' color and highlight codes. It also works in 'Emacs' 'ESS'. 'ANSI' color support is automatically detected. Colors and highlighting can be combined and nested. New styles can also be created easily. This package was inspired by the 'chalk' 'JavaScript' project.

Maintained by Gábor Csárdi. Last updated 5 months ago.

3.3 match 324 stars 16.61 score 1.5k scripts 6.0k dependents

fishr-core-team

FSAdata:Data to Support Fish Stock Assessment ('FSA') Package

The datasets to support the Fish Stock Assessment ('FSA') package.

Maintained by Derek Ogle. Last updated 2 years ago.

fish fisheries fisheries-stock-assessment fishr-website stock-assessment

8.7 match 13 stars 5.75 score 285 scripts

hrbrmstr

hrbrthemes:Additional Themes, Theme Components and Utilities for 'ggplot2'

A compilation of extra 'ggplot2' themes, scales and utilities, including a spell check function for plot label fields and an overall emphasis on typography. A copy of the 'Google' font 'Roboto Condensed' is also included.

Maintained by Bob Rudis. Last updated 2 days ago.

data-visualization datavisualization ggplot-extension ggplot2 ggplot2-scales ggplot2-themes visualization

3.4 match 1.3k stars 13.92 score 13k scripts 15 dependents

worldbank

blackmarbler:Black Marble Data and Statistics

Geographically referenced data and statistics of nighttime lights from NASA Black Marble <https://blackmarble.gsfc.nasa.gov/>.

Maintained by Robert Marty. Last updated 19 days ago.

nasa nasa-data nasa-earth-data nighttime-lights raster-data viirs worldbank zonal-statistics

7.3 match 19 stars 6.13 score 47 scripts

erictleung

pyblack:Style Python code blocks with black

RStudio addin to help format and style Python code in RMarkdown and Quarto documents with the Python code formatter, black.

Maintained by Eric Leung. Last updated 9 months ago.

black formatting python rstudio rstudio-addin

16.3 match 8 stars 2.60 score

nickch-k

causaldata:Example Data Sets for Causal Inference Textbooks

Example data sets to run the example problems from causal inference textbooks. Currently, contains data sets for Huntington-Klein, Nick (2021) "The Effect" <https://theeffectbook.net>, first and second edition, Cunningham, Scott (2021, ISBN-13: 978-0-300-25168-5) "Causal Inference: The Mixtape", and Hernán, Miguel and James Robins (2020) "Causal Inference: What If" <https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/>.

Maintained by Nick Huntington-Klein. Last updated 4 months ago.

5.6 match 136 stars 7.43 score 144 scripts 1 dependents

jirotubuyaki

Jdmbs:Monte Carlo Option Pricing Algorithms for Jump Diffusion Models with Correlational Companies

Option is a one of the financial derivatives and its pricing is an important problem in practice. The process of stock prices are represented as Geometric Brownian motion [Black (1973) <doi:10.1086/260062>] or jump diffusion processes [Kou (2002) <doi:10.1287/mnsc.48.8.1086.166>]. In this package, algorithms and visualizations are implemented by Monte Carlo method in order to calculate European option price for three equations by Geometric Brownian motion and jump diffusion processes and furthermore a model that presents jumps among companies affect each other.

Maintained by Masashi Okada. Last updated 5 years ago.

black-scholes brownian-motion computational-finance derivatives finance financial-analysis financial-engineering jump-diffusion monte-carlo option option-pricing sde stochastic-differential-equations stochastic-processes stock-market

8.0 match 28 stars 5.15 score 6 scripts

ablack3

icdpicr:'ICD' Programs for Injury Categorization in R

Categorization and scoring of injury severity typically involves trained personnel with access to injured persons or their medical records. 'icdpicr' contains a function that provides automated calculation of Abbreviated Injury Scale ('AIS') and Injury Severity Score ('ISS') from International Classification of Diseases ('ICD') codes and may be a useful substitute to manual injury severity scoring. 'ICDPIC' was originally developed in 'Stata', and 'icdpicr' is an open-access update that accepts both 'ICD-9' and 'ICD-10' codes.

Maintained by Adam Black. Last updated 3 years ago.

injury-categorization

9.2 match 6 stars 4.48 score 10 scripts

rempsyc

rempsyc:Convenience Functions for Psychology

Make your workflow faster and easier. Easily customizable plots (via 'ggplot2'), nice APA tables (following the style of the *American Psychological Association*) exportable to Word (via 'flextable'), easily run statistical tests or check assumptions, and automatize various other tasks.

Maintained by Rémi Thériault. Last updated 1 months ago.

convenience-functions ggplot2 psychology statistics visualization

3.6 match 43 stars 10.68 score 214 scripts 2 dependents

cran

ragtop:Pricing Equity Derivatives with Extensions of Black-Scholes

Algorithms to price American and European equity options, convertible bonds and a variety of other financial derivatives. It uses an extension of the usual Black-Scholes model in which jump to default may occur at a probability specified by a power-law link between stock price and hazard rate as found in the paper by Takahashi, Kobayashi, and Nakagawa (2001) <doi:10.3905/jfi.2001.319302>. We use ideas and techniques from Andersen and Buffum (2002) <doi:10.2139/ssrn.355308> and Linetsky (2006) <doi:10.1111/j.1467-9965.2006.00271.x>.

Maintained by Brian K. Boonstra. Last updated 5 years ago.

13.4 match 2.70 score

rsbivand

splancs:Spatial and Space-Time Point Pattern Analysis

The Splancs package was written as an enhancement to S-Plus for display and analysis of spatial point pattern data; it has been ported to R and is in "maintenance mode".

Maintained by Roger Bivand. Last updated 10 months ago.

fortran

4.0 match 1 stars 8.72 score 592 scripts 53 dependents

alanarnholt

BSDA:Basic Statistics and Data Analysis

Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.

Maintained by Alan T. Arnholt. Last updated 2 years ago.

3.8 match 7 stars 9.11 score 1.3k scripts 6 dependents

hneth

unicol:The Colors of your University

Most universities use specific color combinations to express their unique brand identity. The 'unicol' package provides the colors and color palettes of various universities for easy plotting and printing in R. We collect and provide a diverse range of color palettes for creating scientific visualizations.

Maintained by Hansjoerg Neth. Last updated 7 months ago.

branding color color-palettes color-schemes corporate-design university-colors visual-identity

5.2 match 9 stars 6.58 score 10 scripts

nzilbb

nzilbb.vowels:Vowel Covariation Tools

Tools to support research on vowel covariation. Methods are provided to support Principal Component Analysis workflows (as in Brand et al. (2021) <doi:10.1016/j.wocn.2021.101096> and Wilson Black et al. (2023) <doi:10.1515/lingvan-2022-0086>).

Maintained by Joshua Wilson Black. Last updated 3 months ago.

8.7 match 3.88 score 15 scripts

re2simlab

ViSiElse:A Visual Tool for Behavior Analysis over Time

A graphical R package designed to visualize behavioral observations over time. Based on raw time data extracted from video recorded sessions of experimental observations, ViSiElse grants a global overview of a process by combining the visualization of multiple actions timestamps for all participants in a single graph. Individuals and/or group behavior can easily be assessed. Supplementary features allow users to further inspect their data by adding summary statistics (mean, standard deviation, quantile or statistical test) and/or time constraints to assess the accuracy of the realized actions.

Maintained by Elodie Garnier. Last updated 5 years ago.

7.7 match 2 stars 4.34 score 11 scripts

d-acharya

Dowd:Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's Book Measuring Market Risk

'Kevin Dowd's' book Measuring Market Risk is a widely read book in the area of risk measurement by students and practitioners alike. As he claims, 'MATLAB' indeed might have been the most suitable language when he originally wrote the functions, but, with growing popularity of R it is not entirely valid. As 'Dowd's' code was not intended to be error free and were mainly for reference, some functions in this package have inherited those errors. An attempt will be made in future releases to identify and correct them. 'Dowd's' original code can be downloaded from www.kevindowd.org/measuring-market-risk/. It should be noted that 'Dowd' offers both 'MMR2' and 'MMR1' toolboxes. Only 'MMR2' was ported to R. 'MMR2' is more recent version of 'MMR1' toolbox and they both have mostly similar function. The toolbox mainly contains different parametric and non parametric methods for measurement of market risk as well as backtesting risk measurement methods.

Maintained by Dinesh Acharya. Last updated 9 years ago.

10.2 match 3.19 score 154 scripts

tpourmohamad

CompModels:Pseudo Computer Models for Optimization

A suite of computer model test functions that can be used to test and evaluate algorithms for Bayesian (also known as sequential) optimization. Some of the functions have known functional forms, however, most are intended to serve as black-box functions where evaluation requires running computer code that reveals little about the functional forms of the objective and/or constraints. The primary goal of the package is to provide users (especially those who do not have access to real computer models) a source of reproducible and shareable examples that can be used for benchmarking algorithms. The package is a living repository, and so more functions will be added over time. For function suggestions, please do contact the author of the package.

Maintained by Tony Pourmohamad. Last updated 2 years ago.

13.6 match 2.30 score 4 scripts

edzer

sp:Classes and Methods for Spatial Data

Classes and methods for spatial data; the classes document where the spatial location information resides, for 2D or 3D data. Utility functions are provided, e.g. for plotting data as maps, spatial selection, as well as methods for retrieving coordinates, for subsetting, print, summary, etc. From this version, 'rgdal', 'maptools', and 'rgeos' are no longer used at all, see <https://r-spatial.org/r/2023/05/15/evolution4.html> for details.

Maintained by Edzer Pebesma. Last updated 2 months ago.

1.6 match 127 stars 18.63 score 35k scripts 1.3k dependents

paul-buerkner

brms:Bayesian Regression Models using 'Stan'

Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include both theory-driven and data-driven non-linear terms, auto-correlation structures, censoring and truncation, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their prior knowledge. Models can easily be evaluated and compared using several methods assessing posterior or prior predictions. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Bürkner (2018) <doi:10.32614/RJ-2018-017>; Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

Maintained by Paul-Christian Bürkner. Last updated 3 days ago.

bayesian-inference brms multilevel-models stan statistical-models

1.8 match 1.3k stars 16.61 score 13k scripts 34 dependents

eldarrak

FLightR:Reconstruct Animal Paths from Solar Geolocation Loggers Data

Spatio-temporal locations of an animal are computed from annotated data with a hidden Markov model via particle filter algorithm. The package is relatively robust to varying degrees of shading. The hidden Markov model is described in Movement Ecology - Rakhimberdiev et al. (2015) <doi:10.1186/s40462-015-0062-5>, general package description is in the Methods in Ecology and Evolution - Rakhimberdiev et al. (2017) <doi:10.1111/2041-210X.12765> and package accuracy assessed in the Journal of Avian Biology - Rakhimberdiev et al. (2016) <doi:10.1111/jav.00891>.

Maintained by Eldar Rakhimberdiev. Last updated 6 months ago.

movement-ecology solar-geolocation-loggers solar-geolocator

4.0 match 22 stars 7.26 score 111 scripts

reckziegel

epo:Enhanced Portfolio Optimization (EPO)

Implements the Enhanced Portfolio Optimization (EPO) method as described in Pedersen, Babu and Levine (2021) <doi:10.2139/ssrn.3530390>.

Maintained by Bernardo Reckziegel. Last updated 1 years ago.

bayesian-optimization black-litterman mean-variance-optimization principal-component-analysis robust-optimization

7.5 match 10 stars 3.70 score 4 scripts

kenkellner

IPMbook:Functions and Data for the Book 'Integrated Population Models'

Provides functions and data sets to accompany the book 'Integrated Population Models: Theory and Ecological Applications with R and JAGS' by Michael Schaub and Marc Kéry (ISBN: 9780128205648).

Maintained by Ken Kellner. Last updated 1 months ago.

6.9 match 1 stars 3.95 score 177 scripts

distancedevelopment

mrds:Mark-Recapture Distance Sampling

Animal abundance estimation via conventional, multiple covariate and mark-recapture distance sampling (CDS/MCDS/MRDS). Detection function fitting is performed via maximum likelihood. Also included are diagnostics and plotting for fitted detection functions. Abundance estimation is via a Horvitz-Thompson-like estimator.

Maintained by Laura Marshall. Last updated 2 months ago.

3.4 match 4 stars 8.05 score 78 scripts 7 dependents

niehs

amadeus:Accessing and Analyzing Large-Scale Environmental Data

Functions are designed to facilitate access to and utility with large scale, publicly available environmental data in R. The package contains functions for downloading raw data files from web URLs (download_data()), processing the raw data files into clean spatial objects (process_covariates()), and extracting values from the spatial data objects at point and polygon locations (calculate_covariates()). These functions call a series of source-specific functions which are tailored to each data sources/datasets particular URL structure, data format, and spatial/temporal resolution. The functions are tested, versioned, and open source and open access. For sum_edc() method details, see Messier, Akita, and Serre (2012) <doi:10.1021/es203152a>.

Maintained by Kyle Messier. Last updated 19 days ago.

3.5 match 8 stars 7.16 score 13 scripts

epijim

notifyme:Send Alerts to your Cellphone and Phillips Hue Lights

Functions to flash your hue lights, or text yourself, from R. Designed to be used with long running scripts.

Maintained by James Black. Last updated 8 years ago.

9.3 match 1 stars 2.70 score 7 scripts

hneth

riskyr:Rendering Risk Literacy more Transparent

Risk-related information (like the prevalence of conditions, the sensitivity and specificity of diagnostic tests, or the effectiveness of interventions or treatments) can be expressed in terms of frequencies or probabilities. By providing a toolbox of corresponding metrics and representations, 'riskyr' computes, translates, and visualizes risk-related information in a variety of ways. Adopting multiple complementary perspectives provides insights into the interplay between key parameters and renders teaching and training programs on risk literacy more transparent.

Maintained by Hansjoerg Neth. Last updated 10 months ago.

2x2-matrix bayesian-inference contingency-table representation risk risk-literacy visualization

3.4 match 19 stars 7.36 score 80 scripts

sanfordweisberg

alr4:Data to Accompany Applied Linear Regression 4th Edition

Datasets to Accompany S. Weisberg (2014, ISBN: 978-1-118-38608-8), "Applied Linear Regression," 4th edition. Many data files in this package are included in the `alr3` package as well, so only one of them should be used.

Maintained by Sanford Weisberg. Last updated 7 years ago.

7.3 match 1 stars 3.45 score 306 scripts

jakobbossek

ecr:Evolutionary Computation in R

Framework for building evolutionary algorithms for both single- and multi-objective continuous or discrete optimization problems. A set of predefined evolutionary building blocks and operators is included. Moreover, the user can easily set up custom objective functions, operators, building blocks and representations sticking to few conventions. The package allows both a black-box approach for standard tasks (plug-and-play style) and a much more flexible white-box approach where the evolutionary cycle is written by hand.

Maintained by Jakob Bossek. Last updated 1 years ago.

combinatorial-optimization evolutionary-algorithm evolutionary-algorithms evolutionary-strategy genetic-algorithm-framework metaheuristics multi-objective-optimization optimization optimization-framework cpp

3.2 match 43 stars 7.36 score 89 scripts 2 dependents

sammo3182

drhutools:Political Science Academic Research Gears

Using these tools to simplify the research process of political science and other social sciences. The current version can create folder system for academic project in political science, calculate psychological trait scores, visualize experimental and spatial data, and set up color-blind palette, functions used in academic research of political psychology or political science in general.

Maintained by Yue Hu. Last updated 3 months ago.

5.3 match 2 stars 4.45 score 3 scripts

modeloriented

live:Local Interpretable (Model-Agnostic) Visual Explanations

Interpretability of complex machine learning models is a growing concern. This package helps to understand key factors that drive the decision made by complicated predictive model (so called black box model). This is achieved through local approximations that are either based on additive regression like model or CART like model that allows for higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>. More details can be found in Staniak, Biecek (2018) <doi:10.32614/RJ-2018-072>.

Maintained by Mateusz Staniak. Last updated 6 years ago.

iml interpretability lime machine-learning model-visualization visual-explanations xai

3.9 match 35 stars 5.59 score 55 scripts

larmarange

ggstats:Extension to 'ggplot2' for Plotting Stats

Provides new statistics, new geometries and new positions for 'ggplot2' and a suite of functions to facilitate the creation of statistical plots.

Maintained by Joseph Larmarange. Last updated 6 days ago.

1.7 match 37 stars 13.08 score 190 scripts 156 dependents

mayer79

flashlight:Shed Light on Black Box Machine Learning Models

Shed light on black box machine learning models by the help of model performance, variable importance, global surrogate models, ICE profiles, partial dependence (Friedman J. H. (2001) <doi:10.1214/aos/1013203451>), accumulated local effects (Apley D. W. (2016) <arXiv:1612.08468>), further effects plots, interaction strength, and variable contribution breakdown (Gosiewska and Biecek (2019) <arxiv:1903.11420>). All tools are implemented to work with case weights and allow for stratified analysis. Furthermore, multiple flashlights can be combined and analyzed together.

Maintained by Michael Mayer. Last updated 8 months ago.

interpretability interpretable-machine-learning machine-learning xai

3.4 match 22 stars 6.25 score 54 scripts 1 dependents

cran

FinancialMath:Financial Mathematics for Actuaries

Contains financial math functions and introductory derivative functions included in the Society of Actuaries and Casualty Actuarial Society 'Financial Mathematics' exam, and some topics in the 'Models for Financial Economics' exam.

Maintained by Kameron Penn. Last updated 8 years ago.

12.9 match 4 stars 1.60 score

modeloriented

rSAFE:Surrogate-Assisted Feature Extraction

Provides a model agnostic tool for white-box model trained on features extracted from a black-box model. For more information see: Gosiewska et al. (2020) <doi:10.1016/j.dss.2021.113556>.

Maintained by Alicja Gosiewska. Last updated 3 years ago.

feature-engineering feature-extraction iml interpretability machine-learning xai

3.0 match 28 stars 6.79 score 44 scripts

glenndavis52

colorscience:Color Science Methods and Data

Methods and data for color science - color conversions by observer, illuminant, and gamma. Color matching functions and chromaticity diagrams. Color indices, color differences, and spectral data conversion/analysis. This package is deprecated and will someday be removed; for reasons and details please see the README file.

Maintained by Glenn Davis. Last updated 11 months ago.

5.2 match 4 stars 3.93 score 214 scripts

karlines

shape:Functions for Plotting Graphical Shapes, Colors

Functions for plotting graphical shapes such as ellipses, circles, cylinders, arrows, ...

Maintained by Karline Soetaert. Last updated 1 years ago.

1.9 match 10.86 score 984 scripts 1.4k dependents

sachaepskamp

qgraph:Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation

Fork of qgraph - Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.

Maintained by Sacha Epskamp. Last updated 1 years ago.

cpp

1.8 match 69 stars 11.43 score 1.2k scripts 63 dependents

kwstat

pals:Color Palettes, Colormaps, and Tools to Evaluate Them

A comprehensive collection of color palettes, colormaps, and tools to evaluate them. See Kovesi (2015) <doi:10.48550/arXiv.1509.03700>.

Maintained by Kevin Wright. Last updated 9 days ago.

1.7 match 83 stars 11.39 score 2.1k scripts 8 dependents

rmcd1024

derivmkts:Functions and R Code to Accompany Derivatives Markets

A set of pricing and expository functions that should be useful in teaching a course on financial derivatives.

Maintained by Robert McDonald. Last updated 3 years ago.

3.7 match 36 stars 5.13 score 75 scripts

boennecd

DtD:Distance to Default

Provides fast methods to work with Merton's distance to default model introduced in Merton (1974) <doi:10.1111/j.1540-6261.1974.tb03058.x>. The methods includes simulation and estimation of the parameters.

Maintained by Benjamin Christoffersen. Last updated 4 years ago.

blackscholes default finance cpp

3.6 match 5 stars 5.09 score 49 scripts

pecanproject

PEcAn.DB:PEcAn Functions Used for Ecological Forecasts and Reanalysis

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.

Maintained by David LeBauer. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

1.5 match 216 stars 11.88 score 127 scripts 27 dependents

rudeboybert

resampledata:Data Sets for Mathematical Statistics with Resampling in R

Package of data sets from "Mathematical Statistics with Resampling in R" (1st Ed. 2011, 2nd Ed. 2018) by Laura Chihara and Tim Hesterberg.

Maintained by Albert Y. Kim. Last updated 4 months ago.

3.5 match 15 stars 5.15 score 187 scripts

jlaake

RMark:R Code for Mark Analysis

An interface to the software package MARK that constructs input files for MARK and extracts the output. MARK was developed by Gary White and is freely available at <http://www.phidot.org/software/mark/downloads/> but is not open source.

Maintained by Jeff Laake. Last updated 3 years ago.

3.6 match 4.90 score 366 scripts 4 dependents

plangfelder

WGCNA:Weighted Correlation Network Analysis

Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.

Maintained by Peter Langfelder. Last updated 6 months ago.

cpp

1.8 match 54 stars 9.65 score 5.3k scripts 32 dependents

pecanproject

PEcAn.utils:PEcAn Functions Used for Ecological Forecasts and Reanalysis

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PEcAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.

Maintained by Rob Kooper. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

1.5 match 216 stars 10.92 score 218 scripts 35 dependents

bioc

clustifyr:Classifier for Single-cell RNA-seq Using Cell Clusters

Package designed to aid in classifying cells from single-cell RNA sequencing data using external reference data (e.g., bulk RNA-seq, scRNA-seq, microarray, gene lists). A variety of correlation based methods and gene list enrichment methods are provided to assist cell type assignment.

Maintained by Rui Fu. Last updated 5 months ago.

singlecell annotation sequencing microarray geneexpression assign-identities clusters marker-genes rna-seq single-cell-rna-seq

1.8 match 119 stars 9.63 score 296 scripts

rbgramacy

tgp:Bayesian Treed Gaussian Process Models

Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes (GPs) with jumps to the limiting linear model (LLM). Special cases also implemented include Bayesian linear models, CART, treed linear models, stationary separable and isotropic GPs, and GP single-index models. Provides 1-d and 2-d plotting functions (with projection and slice capabilities) and tree drawing, designed for visualization of tgp-class output. Sensitivity analysis and multi-resolution models are supported. Sequential experimental design and adaptive sampling functions are also provided, including ALM, ALC, and expected improvement. The latter supports derivative-free optimization of noisy black-box functions. For details and tutorials, see Gramacy (2007) <doi:10.18637/jss.v019.i09> and Gramacy & Taddy (2010) <doi:10.18637/jss.v033.i06>.

Maintained by Robert B. Gramacy. Last updated 6 months ago.

openblas cpp

2.2 match 9 stars 7.36 score 203 scripts 12 dependents

lightbluetitan

educationR:A Comprehensive Collection of Educational Datasets

Provides a comprehensive collection of datasets related to education, covering topics such as student performance, learning methods, test scores, absenteeism, and other educational metrics. This package is designed as a resource for educational researchers, data analysts, and statisticians to explore and analyze data in the field of education.

Maintained by Renzo Caceres Rossi. Last updated 3 months ago.

3.8 match 4 stars 4.30 score 3 scripts

misstiny

PIE:A Partially Interpretable Model with Black-Box Refinement

Implements a novel predictive model, Partially Interpretable Estimators (PIE), which jointly trains an interpretable model and a black-box model to achieve high predictive performance as well as partial model. See the paper, Wang, Yang, Li, and Wang (2021) <doi:10.48550/arXiv.2105.02410>.

Maintained by Jingyi Yang. Last updated 2 months ago.

8.0 match 2.00 score

kbroman

broman:Karl Broman's R Code

Miscellaneous R functions, including functions related to graphics (mostly for base graphics), permutation tests, running mean/median, and general utilities.

Maintained by Karl W Broman. Last updated 10 months ago.

1.8 match 183 stars 8.80 score 648 scripts 1 dependents

pavel-fibich

TRADER:Tree Ring Analysis of Disturbance Events in R

Tree Ring Analysis of Disturbance Events in R (TRADER) package provides functions for disturbance reconstruction from tree-ring data, e.g. boundary line, absolute increase, growth averaging methods.

Maintained by Pavel Fibich. Last updated 1 months ago.

3.3 match 5 stars 4.74 score 37 scripts

spiritspeak

rapidsplithalf:A Fast Permutation-Based Split-Half Reliability Algorithm

Accurately estimates the reliability of cognitive tasks using a fast and flexible permutation-based split-half reliability algorithm that supports stratified splitting while maintaining equal split sizes. See Kahveci, Bathke, and Blechert (2022) <doi:10.31234/osf.io/ta59r> for details.

Maintained by Sercan Kahveci. Last updated 11 days ago.

cpp

3.3 match 4.78 score 5 scripts

pecanproject

PEcAn.BIOCRO:PEcAn Package for Integration of the BioCro Model

This module provides functions to link BioCro to PEcAn.

Maintained by David LeBauer. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants jags cpp

1.8 match 216 stars 8.92 score 23 scripts

biagolini

bwimage:Describe Image Patterns in Natural Structures

A computational tool to describe patterns in black and white images from natural structures. 'bwimage' implemented functions for exceptionally broad subject. For instance, 'bwimage' provide examples that range from calculation of canopy openness, description of patterns in vertical vegetation structure, to patterns in bird nest structure.

Maintained by Carlos Biagolini-Jr.. Last updated 5 years ago.

4.2 match 3.70 score

cran

ei:Ecological Inference

Software accompanying Gary King's book: A Solution to the Ecological Inference Problem. (1997). Princeton University Press. ISBN 978-0691012407.

Maintained by James Honaker. Last updated 8 years ago.

7.8 match 1 stars 2.00 score

tylermorganwall

rayimage:Image Processing for Simulated Cameras

Uses convolution-based techniques to generate simulated camera bokeh, depth of field, and other camera effects, using an image and an optional depth map. Accepts both filename inputs and in-memory array representations of images and matrices. Includes functions to perform 2D convolutions, reorient and resize images/matrices, add image and text overlays, generate camera vignette effects, and add titles to images.

Maintained by Tyler Morgan-Wall. Last updated 1 months ago.

cpp

2.0 match 52 stars 7.67 score 22 scripts 12 dependents

johnjsl7

daewr:Design and Analysis of Experiments with R

Contains Data frames and functions used in the book "Design and Analysis of Experiments with R", Lawson(2015) ISBN-13:978-1-4398-6813-3.

Maintained by John Lawson. Last updated 2 years ago.

4.0 match 3 stars 3.83 score 217 scripts 3 dependents

pecanproject

PEcAn.logger:Logger Functions for 'PEcAn'

Convenience functions for logging outputs from 'PEcAn', the Predictive Ecosystem Analyzer (LeBauer et al. 2017) <doi:10.1890/12-0137.1>. Enables the user to set what level of messages are printed, as well as whether these messages are written to the console, a file, or both. It also allows control over whether severe errors should stop execution of the 'PEcAn' workflow; this allows strictness when debugging and lenience when running large batches of simulations that should not be terminated by errors in individual models. It is loosely based on the 'log4j' package.

Maintained by Rob Kooper. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

1.6 match 216 stars 9.64 score 7 scripts 40 dependents

darwin-eu

omopgenerics:Methods and Classes for the OMOP Common Data Model

Provides definitions of core classes and methods used by analytic pipelines that query the OMOP (Observational Medical Outcomes Partnership) common data model.

Maintained by Martí Català. Last updated 10 days ago.

1.5 match 9.97 score 193 scripts 16 dependents

cbielow

PTXQC:Quality Report Generation for MaxQuant and mzTab Results

Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the MaxQuant software suite (from .txt files) or mzTab files (ideally from OpenMS 'QualityControl' tool). Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) <doi:10.1021/acs.jproteome.5b00780>.

Maintained by Chris Bielow. Last updated 1 years ago.

drag-and-drop hacktoberfest heatmap match-between-runs maxquant metric mztab openms proteomics quality-control quality-metrics report

1.6 match 42 stars 9.35 score 105 scripts 1 dependents

pecanproject

PEcAn.remote:PEcAn Model Execution Utilities

This package contains utilities for communicating with and executing code on local and remote hosts. In particular, it has PEcAn-specific utilities for starting ecosystem model runs.

Maintained by Rob Kooper. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

1.6 match 216 stars 9.66 score 13 scripts 32 dependents

birdscanada

naturecounts:Access and download data on plant and animal populations from NatureCounts

Access and download data on plant and animal populations from various databases through NatureCounts, a service managed by Bird Studies Canada.

Maintained by Denis Lepage. Last updated 6 months ago.

3.6 match 14 stars 4.11 score 46 scripts

fraenzi

blmeco:Data Files and Functions Accompanying the Book "Bayesian Data Analysis in Ecology using R, BUGS and Stan"

Data files and functions accompanying the book Korner-Nievergelt, Roth, von Felten, Guelat, Almasi, Korner-Nievergelt (2015) "Bayesian Data Analysis in Ecology using R, BUGS and Stan", Elsevier, New York.

Maintained by Fraenzi Korner-Nievergelt. Last updated 5 years ago.

3.6 match 4.05 score 111 scripts

ohdsi

Andromeda:Asynchronous Disk-Based Representation of Massive Data

Storing very large data objects on a local drive, while still making it possible to manipulate the data in an efficient manner.

Maintained by Martijn Schuemie. Last updated 7 months ago.

hades

1.6 match 11 stars 9.18 score 57 scripts 7 dependents

fate-ewi

bayesdfa:Bayesian Dynamic Factor Analysis (DFA) with 'Stan'

Implements Bayesian dynamic factor analysis with 'Stan'. Dynamic factor analysis is a dimension reduction tool for multivariate time series. 'bayesdfa' extends conventional dynamic factor models in several ways. First, extreme events may be estimated in the latent trend by modeling process error with a student-t distribution. Second, alternative constraints (including proportions are allowed). Third, the estimated dynamic factors can be analyzed with hidden Markov models to evaluate support for latent regimes.

Maintained by Eric J. Ward. Last updated 5 months ago.

cpp

1.8 match 28 stars 8.28 score 101 scripts

usaid-oha-si

glitr:Adorned SI style plots

Helps create and export ggplot2 charts in the style used by the GH OHA SI team. Includes multiple styles and themes to tweak plots to user needs. Sample testing data also available.

Maintained by Tim Essam. Last updated 3 months ago.

2.3 match 27 stars 6.43 score 279 scripts 1 dependents

pecanproject

PEcAn.photosynthesis:PEcAn functions used for leaf-level photosynthesis calculations

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PECAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation. The PEcAn.photosynthesis package contains functions used in the Hierarchical Bayesian calibration of the Farquhar et al 1980 model.

Maintained by Mike Dietze. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants jags cpp

1.6 match 216 stars 8.84 score 19 scripts

mclements

collett:Datasets from "Modelling Survival Data in Medical Research" by Collett

Datasets for the book entitled "Modelling Survival Data in Medical Research" by Collett (2023) <doi:10.1201/9781003282525>. The datasets provide extensive examples of time-to-event data.

Maintained by Mark Clements. Last updated 2 months ago.

4.0 match 2 stars 3.48 score 1 scripts

jianhong

colorBlindness:Safe Color Set for Color Blindness

Provide the safe color set for color blindness, the simulator of protanopia, deuteranopia. The color sets are collected from: Wong, B. (2011) <doi:10.1038/nmeth.1618>, and <http://mkweb.bcgsc.ca/biovis2012/>. The simulations of the appearance of the colors to color-deficient viewers were based on algorithms in Vienot, F., Brettel, H. and Mollon, J.D. (1999) <doi:10.1002/(SICI)1520-6378(199908)24:4%3C243::AID-COL5%3E3.0.CO;2-3>. The cvdPlot() function to generate 'ggplot' grobs of simulations were modified from <https://github.com/clauswilke/colorblindr>.

Maintained by Jianhong Ou. Last updated 4 years ago.

visualization

3.3 match 4.20 score 315 scripts

jakobbossek

smoof:Single and Multi-Objective Optimization Test Functions

Provides generators for a high number of both single- and multi- objective test functions which are frequently used for the benchmarking of (numerical) optimization algorithms. Moreover, it offers a set of convenient functions to generate, plot and work with objective functions.

Maintained by Jakob Bossek. Last updated 1 years ago.

benchmark-functions multi-objective-optimization single-objective-optimization cpp

1.6 match 36 stars 8.54 score 261 scripts 9 dependents

bioc

Heatplus:Heatmaps with row and/or column covariates and colored clusters

Display a rectangular heatmap (intensity plot) of a data matrix. By default, both samples (columns) and features (row) of the matrix are sorted according to a hierarchical clustering, and the corresponding dendrogram is plotted. Optionally, panels with additional information about samples and features can be added to the plot.

Maintained by Alexander Ploner. Last updated 5 months ago.

microarray visualization

1.8 match 7.63 score 94 scripts 5 dependents

pecanproject

PEcAn.all:PEcAn Functions Used for Ecological Forecasts and Reanalysis

The Predictive Ecosystem Carbon Analyzer (PEcAn) is a scientific workflow management tool that is designed to simplify the management of model parameterization, execution, and analysis. The goal of PEcAn is to streamline the interaction between data and models, and to improve the efficacy of scientific investigation.

Maintained by David LeBauer. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants jags cpp

1.5 match 216 stars 8.99 score 266 scripts

cran

monitoR:Acoustic Template Detection in R

Acoustic template detection and monitoring database interface. Create, modify, save, and use templates for detection of animal vocalizations. View, verify, and extract results. Upload a MySQL schema to a existing instance, manage survey metadata, write and read templates and detections locally or to the database.

Maintained by Sasha D. Hafner. Last updated 7 years ago.

3.4 match 3 stars 3.95 score 5 dependents

cran

matRiks:Generates Raven-Like Matrices According to Rules

Generates Raven like matrices according to different rules and the response list associated to the matrix. The package can generate matrices composed of 4 or 9 cells, along with a response list of 11 elements (the correct response + 10 incorrect responses). The matrices can be generated according to both logical rules (i.e., the relationships between the elements in the matrix are manipulated to create the matrix) and visual-spatial rules (i.e., the visual or spatial characteristics of the elements are manipulated to generate the matrix). The graphical elements of this package are based on the 'DescTools' package. This package has been developed within the PRIN2020 Project (Prot. 20209WKCLL) titled "Computerized, Adaptive and Personalized Assessment of Executive Functions and Fluid Intelligence" and founded by the Italian Ministry of Education and Research.

Maintained by Andrea Brancaccio. Last updated 1 years ago.

3.8 match 3.60 score

aphalo

ggspectra:Extensions to 'ggplot2' for Radiation Spectra

Additional annotations, stats, geoms and scales for plotting "light" spectra with 'ggplot2', together with specializations of ggplot() and autoplot() methods for spectral data and waveband definitions stored in objects of classes defined in package 'photobiology'. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.

Maintained by Pedro J. Aphalo. Last updated 2 days ago.

dataviz ggplot2-autoplot ggplot2-enhancementes ggplot2-geoms ggplot2-scales ggplot2-stats light r4photobiology-suite radiation spectra

1.7 match 5 stars 8.09 score 390 scripts 1 dependents

ropensci

traits:Species Trait Data from Around the Web

Species trait data from many different sources, including sequence data from 'NCBI' (<https://www.ncbi.nlm.nih.gov/>), plant trait data from 'BETYdb', data from 'EOL' 'Traitbank', 'Birdlife' International, and more.

Maintained by David LeBauer. Last updated 2 months ago.

traits api web-services species taxonomy api-client

1.5 match 41 stars 8.65 score 82 scripts 11 dependents

jayemerson

STV:Single Transferable Vote Counting

Implementations of the Single Transferable Vote counting system. By default, it uses the Cambridge method for surplus allocation and Droop method for quota calculation. Fractional surplus allocation and the Hare quota are available as options.

Maintained by John Emerson. Last updated 4 years ago.

3.1 match 3 stars 4.26 score 10 scripts

ruben-hernan

LifeHist:Life History Models of Individuals

Likelihood-based estimation of individual growth and sexual maturity models for organisms, usually fish and invertebrates. It includes methods for data organization, plotting standard exploratory and analytical plots, predictions.

Maintained by Ruben H. Roa-Ureta. Last updated 10 years ago.

10.1 match 1.30 score 20 scripts

sem-in-r

seminr:Building and Estimating Structural Equation Models

A powerful, easy to syntax for specifying and estimating complex Structural Equation Models. Models can be estimated using Partial Least Squares Path Modeling or Covariance-Based Structural Equation Modeling or covariance based Confirmatory Factor Analysis. Methods described in Ray, Danks, and Valdez (2021).

Maintained by Nicholas Patrick Danks. Last updated 3 years ago.

common-factors composites construct pls-models

1.8 match 62 stars 7.46 score 284 scripts

risktoollib

RTL:Risk Tool Library - Trading, Risk, Analytics for Commodities

A toolkit for Commodities 'analytics', risk management and trading professionals. Includes functions for API calls to <https://commodities.morningstar.com/#/>, <https://developer.genscape.com/>, and <https://www.bankofcanada.ca/valet/docs>.

Maintained by Philippe Cote. Last updated 18 days ago.

analytics api commodities commodities-api finance genscape morningstar python risk-management cpp

1.7 match 30 stars 7.51 score 198 scripts

tdhock

directlabels:Direct Labels for Multicolor Plots

An extensible framework for automatically placing direct labels onto multicolor 'lattice' or 'ggplot2' plots. Label positions are described using Positioning Methods which can be re-used across several different plots. There are heuristics for examining "trellis" and "ggplot" objects and inferring an appropriate Positioning Method.

Maintained by Toby Dylan Hocking. Last updated 11 months ago.

1.2 match 83 stars 10.62 score 1.8k scripts 16 dependents

jasono6359

flfishltm:A package for analyzing FL FWC Freshwater long-term monitoring (LTM) data

Provides functions for summarizing and analyzing FL FWC Freshwater Fish Long-term Monitoring Data.

Maintained by Jason OConnor. Last updated 8 months ago.

3.4 match 1 stars 3.70 score

f-rousset

blackbox:Black Box Optimization and Exploration of Parameter Space

Performs prediction of a response function from simulated response values, allowing black-box optimization of functions estimated with some error. Includes a simple user interface for such applications, as well as more specialized functions designed to be called by the Migraine software (Rousset and Leblois, 2012 <doi:10.1093/molbev/MSR262>; Leblois et al., 2014 <doi:10.1093/molbev/msu212>; and see URL). The latter functions are used for prediction of likelihood surfaces and implied likelihood ratio confidence intervals, and for exploration of predictor space of the surface. Prediction of the response is based on ordinary Kriging (with residual error) of the input. Estimation of smoothing parameters is performed by generalized cross-validation.

Maintained by François Rousset. Last updated 1 years ago.

cpp

7.0 match 1.79 score 8 scripts 1 dependents

darwin-eu

IncidencePrevalence:Estimate Incidence and Prevalence using the OMOP Common Data Model

Calculate incidence and prevalence using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. Incidence and prevalence can be estimated for the total population in a database or for a stratification cohort.

Maintained by Edward Burn. Last updated 6 days ago.

1.5 match 9 stars 7.96 score 102 scripts 1 dependents

pecanproject

PEcAn.SIBCASA:PEcAn Package for Integration of the SiBCASA Model

This module provides functions to link (SiBCASA) to PEcAn. It is a work in progress and is not yet fully functional.

Maintained by Rob Kooper. Last updated 2 days ago.

bayesian cyberinfrastructure data-assimilation data-science ecosystem-model ecosystem-science forecasting meta-analysis national-science-foundation pecan plants

1.6 match 216 stars 7.56 score

siacus

sde:Simulation and Inference for Stochastic Differential Equations

Companion package to the book Simulation and Inference for Stochastic Differential Equations With R Examples, ISBN 978-0-387-75838-1, Springer, NY. *

Maintained by Stefano Maria Iacus. Last updated 2 years ago.

1.7 match 7.02 score 178 scripts 15 dependents

pablo14

funModeling:Exploratory Data Analysis and Data Preparation Tool-Box

Around 10% of almost any predictive modeling project is spent in predictive modeling, 'funModeling' and the book Data Science Live Book (<https://livebook.datascienceheroes.com/>) are intended to cover remaining 90%: data preparation, profiling, selecting best variables 'dataViz', assessing model performance and other functions.

Maintained by Pablo Casas. Last updated 2 years ago.

1.3 match 100 stars 8.57 score 654 scripts

aughunter

convertbonds:Use the Given Parameters to Calculate the European Option Value

Calculate the theoretical value of convertible bonds by given parameters, including B-S theory and Monte Carlo method.

Maintained by Tai-Sen Zheng. Last updated 2 years ago.

4.1 match 1 stars 2.70 score

kbhoehn

dowser:B Cell Receptor Phylogenetics Toolkit

Provides a set of functions for inferring, visualizing, and analyzing B cell phylogenetic trees. Provides methods to 1) reconstruct unmutated ancestral sequences, 2) build B cell phylogenetic trees using multiple methods, 3) visualize trees with metadata at the tips, 4) reconstruct intermediate sequences, 5) detect biased ancestor-descendant relationships among metadata types Workflow examples available at documentation site (see URL). Citations: Hoehn et al (2022) <doi:10.1371/journal.pcbi.1009885>, Hoehn et al (2021) <doi:10.1101/2021.01.06.425648>.

Maintained by Kenneth Hoehn. Last updated 2 months ago.

1.6 match 6.81 score 84 scripts

rmheiberger

HH:Statistical Analysis and Data Display: Heiberger and Holland

Support software for Statistical Analysis and Data Display (Second Edition, Springer, ISBN 978-1-4939-2121-8, 2015) and (First Edition, Springer, ISBN 0-387-40270-5, 2004) by Richard M. Heiberger and Burt Holland. This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The second edition includes redesigned graphics and additional chapters. The authors emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. All functions introduced in the book are in the package. R code for all examples, both graphs and tables, in the book is included in the scripts directory of the package.

Maintained by Richard M. Heiberger. Last updated 1 months ago.

1.7 match 3 stars 6.42 score 752 scripts 5 dependents

ghurault

HuraultMisc:Guillem Hurault Functions' Library

Contains various functions for data analysis, notably helpers and diagnostics for Bayesian modelling using Stan.

Maintained by Guillem Hurault. Last updated 3 months ago.

bayesian-statistics data-analysis statistical-models

3.6 match 2.95 score 18 scripts

ohdsi

Eunomia:Standard Dataset Manager for Observational Medical Outcomes Partnership Common Data Model Sample Datasets

Facilitates access to sample datasets from the 'EunomiaDatasets' repository (<https://github.com/ohdsi/EunomiaDatasets>).

Maintained by Frank DeFalco. Last updated 11 months ago.

hades openjdk

1.6 match 43 stars 6.73 score 139 scripts

a2-ai

scicalc:Scientific Calculations for Quantitative Clinical Pharmacology and Pharmacometrics Analysis

Utility functions helpful for reproducible scientific calculations.

Maintained by Matthew Smith. Last updated 1 months ago.

2.6 match 1 stars 4.04 score 4 scripts

gaborcsardi

rcorpora:A Collection of Small Text Corpora of Interesting Data

A collection of small text corpora of interesting data. It contains all data sets from 'dariusk/corpora'. Some examples: names of animals: birds, dinosaurs, dogs; foods: beer categories, pizza toppings; geography: English towns, rivers, oceans; humans: authors, US presidents, occupations; science: elements, planets; words: adjectives, verbs, proverbs, US president quotes.

Maintained by Gábor Csárdi. Last updated 7 years ago.

1.5 match 42 stars 6.83 score 36 scripts 2 dependents

cran

RNCEP:Obtain, Organize, and Visualize NCEP Weather Data

Contains functions to retrieve, organize, and visualize weather data from the NCEP/NCAR Reanalysis (<https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html>) and NCEP/DOE Reanalysis II (<https://psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html>) datasets. Data are queried via the Internet and may be obtained for a specified spatial and temporal extent or interpolated to a point in space and time. We also provide functions to visualize these weather data on a map. There are also functions to simulate flight trajectories according to specified behavior using either NCEP wind data or data specified by the user.

Maintained by Michael U. Kemp. Last updated 2 months ago.

3.4 match 1 stars 2.95 score 90 scripts

mvogel78

childsds:Data and Methods Around Reference Values in Pediatrics

Calculation of standard deviation scores and percentiles adduced from different standards (WHO, UK, Germany, Italy, China, etc). Also, references for laboratory values in children and adults are available, e.g., serum lipids, iron-related blood parameters, IGF, liver enzymes. See package documentation for full list.

Maintained by Mandy Vogel. Last updated 2 months ago.

3.5 match 2.83 score 51 scripts

roliveros-ramos

calibrar:Automated Parameter Estimation for Complex Models

General optimisation and specific tools for the parameter estimation (i.e. calibration) of complex models, including stochastic ones. It implements generic functions that can be used for fitting any type of models, especially those with non-differentiable objective functions, with the same syntax as 'stats::optim()'. It supports multiple phases estimation (sequential parameter masking), constrained optimization (bounding box restrictions) and automatic parallel computation of numerical gradients. Some common maximum likelihood estimation methods and automated construction of the objective function from simulated model outputs is provided. See <https://roliveros-ramos.github.io/calibrar/> for more details.

Maintained by Ricardo Oliveros-Ramos. Last updated 19 days ago.

modeling optimization optimization-methods

1.6 match 7 stars 6.05 score 27 scripts

nschiett

fishualize:Color Palettes Based on Fish Species

Implementation of color palettes based on fish species.

Maintained by Nina M. D. Schiettekatte. Last updated 11 months ago.

1.1 match 155 stars 8.54 score 370 scripts

bioc

seqsetvis:Set Based Visualizations for Next-Gen Sequencing Data

seqsetvis enables the visualization and analysis of sets of genomic sites in next gen sequencing data. Although seqsetvis was designed for the comparison of mulitple ChIP-seq samples, this package is domain-agnostic and allows the processing of multiple genomic coordinate files (bed-like files) and signal files (bigwig files pileups from bam file). seqsetvis has multiple functions for fetching data from regions into a tidy format for analysis in data.table or tidyverse and visualization via ggplot2.

Maintained by Joseph R Boyd. Last updated 3 months ago.

software chipseq multiplecomparison sequencing visualization

1.6 match 5.82 score 82 scripts

rvaradhan

dfoptim:Derivative-Free Optimization

Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.

Maintained by Ravi Varadhan. Last updated 2 years ago.

1.6 match 5.78 score 195 scripts 20 dependents

sjmgarnier

viridis:Colorblind-Friendly Color Maps for R

Color maps designed to improve graph readability for readers with common forms of color blindness and/or color vision deficiency. The color maps are also perceptually-uniform, both in regular form and also when converted to black-and-white for printing. This package also contains 'ggplot2' bindings for discrete and continuous color and fill scales. A lean version of the package called 'viridisLite' that does not include the 'ggplot2' bindings can be found at <https://cran.r-project.org/package=viridisLite>.

Maintained by Simon Garnier. Last updated 1 years ago.

color-blindness color-scheme

0.5 match 299 stars 17.92 score 49k scripts 1.2k dependents

bappa10085

SoilTesting:Organic Carbon and Plant Available Nutrient Contents in Soil

Testing of soil for the contents of organic carbon, and available macro- and micro-nutrients is a crucial part of soil fertility assessment. This package computes some routinely tested soil properties viz. organic carbon (C), total nitrogen (N), available N, mineral N, available phosphorus (P), available potassium (K), available iron (Fe), available zinc (Zn), available manganese (Mn), available copper (Cu), and available nickel (Ni) in soil based on laboratory analysis data obtained by most commonly followed protocols. Besides, it can also draw standard curves based on absorption/emission vs. concentration data, and give out unknown concentrations from absorption/emission readings.

Maintained by Bappa Das. Last updated 1 years ago.

3.3 match 2.70 score 1 scripts

hrbrmstr

epidata:Tools to Retrieve Economic Policy Institute Data Library Extracts

The Economic Policy Institute (<http://www.epi.org/>) provides researchers, media, and the public with easily accessible, up-to-date, and comprehensive historical data on the American labor force. It is compiled from Economic Policy Institute analysis of government data sources. Use it to research wages, inequality, and other economic indicators over time and among demographic groups. Data is usually updated monthly.

Maintained by Bob Rudis. Last updated 5 years ago.

1.6 match 20 stars 5.45 score 28 scripts

fscopaolomancuso

fractD:Estimation of Fractal Dimension of a Black Area in 2D and 3D (Slices) Images

Estimate the of fractal dimension of a black area in 2D and 3D (slices) images using the box-counting method. See Klinkenberg B. (1994) <doi:10.1007/BF02065874>.

Maintained by Francesco Paolo Mancuso. Last updated 4 years ago.

3.3 match 1 stars 2.70 score 4 scripts

cseljatib

datana:Datasets and Functions to Accompany Analisis De Datos Con R

Datasets and functions to accompany the book 'Analisis de datos con el programa estadistico R: una introduccion aplicada' by Salas-Eljatib (2021, ISBN: 9789566086109). The package helps carry out data management, exploratory analyses, and model fitting.

Maintained by Christian Salas-Eljatib. Last updated 6 months ago.

6.8 match 1.30 score 1 scripts

bioc

CNVrd2:CNVrd2: a read depth-based method to detect and genotype complex common copy number variants from next generation sequencing data.

CNVrd2 uses next-generation sequencing data to measure human gene copy number for multiple samples, indentify SNPs tagging copy number variants and detect copy number polymorphic genomic regions.

Maintained by Hoang Tan Nguyen. Last updated 5 months ago.

copynumbervariation snp sequencing software coverage linkagedisequilibrium clustering.jags cpp

1.7 match 3 stars 4.92 score

tomkellygenetics

graphsim:Simulate Expression Data from 'igraph' Networks

Functions to develop simulated continuous data (e.g., gene expression) from a sigma covariance matrix derived from a graph structure in 'igraph' objects. Intended to extend 'mvtnorm' to take 'igraph' structures rather than sigma matrices as input. This allows the use of simulated data that correctly accounts for pathway relationships and correlations. This allows the use of simulated data that correctly accounts for pathway relationships and correlations. Here we present a versatile statistical framework to simulate correlated gene expression data from biological pathways, by sampling from a multivariate normal distribution derived from a graph structure. This package allows the simulation of biological pathways from a graph structure based on a statistical model of gene expression. For example methods to infer biological pathways and gene regulatory networks from gene expression data can be tested on simulated datasets using this framework. This also allows for pathway structures to be considered as a confounding variable when simulating gene expression data to test the performance of genomic analyses.

Maintained by S. Thomas Kelly. Last updated 3 years ago.

benchmarking gene-expression gene-regulatory-networks genetics genomic-data-analysis genomics graph-algorithms igraph-networks joss ngs-analysis simulated-data simulation-modeling

1.6 match 24 stars 5.08 score 2 scripts

cran

CreditRisk:Evaluation of Credit Risk with Structural and Reduced Form Models

Evaluation of default probability of sovereign and corporate entities based on structural or intensity based models and calibration on market Credit Default Swap quotes. References: Damiano Brigo, Massimo Morini, Andrea Pallavicini (2013) <doi:10.1002/9781118818589>. Print ISBN: 9780470748466, Online ISBN: 9781118818589. © 2013 John Wiley & Sons Ltd.

Maintained by Alessandro Cimarelli. Last updated 11 months ago.

5.5 match 3 stars 1.48 score

sjmgarnier

viridisLite:Colorblind-Friendly Color Maps (Lite Version)

Color maps designed to improve graph readability for readers with common forms of color blindness and/or color vision deficiency. The color maps are also perceptually-uniform, both in regular form and also when converted to black-and-white for printing. This is the 'lite' version of the 'viridis' package that also contains 'ggplot2' bindings for discrete and continuous color and fill scales and can be found at <https://cran.r-project.org/package=viridis>.

Maintained by Simon Garnier. Last updated 2 years ago.

color-blindness color-scheme

0.5 match 67 stars 15.75 score 2.3k scripts 8.0k dependents

ftwkoopmans

goat:Gene Set Analysis Using the Gene Set Ordinal Association Test

Perform gene set enrichment analyses using the Gene set Ordinal Association Test (GOAT) algorithm and visualize your results. Koopmans, F. (2024) <doi:10.1038/s42003-024-06454-5>.

Maintained by Frank Koopmans. Last updated 22 days ago.

bioinformatics geneset-enrichment geneset-enrichment-analysis cpp openmp

1.8 match 10 stars 4.40 score 8 scripts

mariushofert

qrmtools:Tools for Quantitative Risk Management

Functions and data sets for reproducing selected results from the book "Quantitative Risk Management: Concepts, Techniques and Tools". Furthermore, new developments and auxiliary functions for Quantitative Risk Management practice.

Maintained by Marius Hofert. Last updated 1 years ago.

1.9 match 2 stars 4.15 score 237 scripts

modeloriented

localModel:LIME-Based Explanations with Interpretable Inputs Based on Ceteris Paribus Profiles

Local explanations of machine learning models describe, how features contributed to a single prediction. This package implements an explanation method based on LIME (Local Interpretable Model-agnostic Explanations, see Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>) in which interpretable inputs are created based on local rather than global behaviour of each original feature.

Maintained by Przemyslaw Biecek. Last updated 3 years ago.

1.3 match 14 stars 6.16 score 23 scripts

atkinsjeff

forestr:Ecosystem and Canopy Structural Complexity Metrics from LiDAR

Provides a toolkit for calculating forest and canopy structural complexity metrics from terrestrial LiDAR (light detection and ranging). References: Atkins et al. 2018 <doi:10.1111/2041-210X.13061>; Hardiman et al. 2013 <doi:10.3390/f4030537>; Parker et al. 2004 <doi:10.1111/j.0021-8901.2004.00925.x>.

Maintained by Jeff Atkins. Last updated 1 years ago.

1.6 match 29 stars 4.95 score 31 scripts

lala-s-riza

metaheuristicOpt:Metaheuristic for Optimization

An implementation of metaheuristic algorithms for continuous optimization. Currently, the package contains the implementations of 21 algorithms, as follows: particle swarm optimization (Kennedy and Eberhart, 1995), ant lion optimizer (Mirjalili, 2015 <doi:10.1016/j.advengsoft.2015.01.010>), grey wolf optimizer (Mirjalili et al., 2014 <doi:10.1016/j.advengsoft.2013.12.007>), dragonfly algorithm (Mirjalili, 2015 <doi:10.1007/s00521-015-1920-1>), firefly algorithm (Yang, 2009 <doi:10.1007/978-3-642-04944-6_14>), genetic algorithm (Holland, 1992, ISBN:978-0262581110), grasshopper optimisation algorithm (Saremi et al., 2017 <doi:10.1016/j.advengsoft.2017.01.004>), harmony search algorithm (Mahdavi et al., 2007 <doi:10.1016/j.amc.2006.11.033>), moth flame optimizer (Mirjalili, 2015 <doi:10.1016/j.knosys.2015.07.006>, sine cosine algorithm (Mirjalili, 2016 <doi:10.1016/j.knosys.2015.12.022>), whale optimization algorithm (Mirjalili and Lewis, 2016 <doi:10.1016/j.advengsoft.2016.01.008>), clonal selection algorithm (Castro, 2002 <doi:10.1109/TEVC.2002.1011539>), differential evolution (Das & Suganthan, 2011), shuffled frog leaping (Eusuff, Landsey & Pasha, 2006), cat swarm optimization (Chu et al., 2006), artificial bee colony algorithm (Karaboga & Akay, 2009), krill-herd algorithm (Gandomi & Alavi, 2012), cuckoo search (Yang & Deb, 2009), bat algorithm (Yang, 2012), gravitational based search (Rashedi et al., 2009) and black hole optimization (Hatamlou, 2013).

Maintained by Lala Septem Riza. Last updated 6 years ago.

2.3 match 4 stars 3.38 score 66 scripts 3 dependents

bioc

SpatialOmicsOverlay:Spatial Overlay for Omic Data from Nanostring GeoMx Data

Tools for NanoString Technologies GeoMx Technology. Package to easily graph on top of an OME-TIFF image. Plotting annotations can range from tissue segment to gene expression.

Maintained by Maddy Griswold. Last updated 5 months ago.

geneexpression transcription cellbasedassays dataimport transcriptomics proteomics proprietaryplatforms rnaseq spatial datarepresentation visualization openjdk

1.8 match 4.30 score 8 scripts

bioc

InterCellar:InterCellar: an R-Shiny app for interactive analysis and exploration of cell-cell communication in single-cell transcriptomics

InterCellar is implemented as an R/Bioconductor Package containing a Shiny app that allows users to interactively analyze cell-cell communication from scRNA-seq data. Starting from precomputed ligand-receptor interactions, InterCellar provides filtering options, annotations and multiple visualizations to explore clusters, genes and functions. Finally, based on functional annotation from Gene Ontology and pathway databases, InterCellar implements data-driven analyses to investigate cell-cell communication in one or multiple conditions.

Maintained by Marta Interlandi. Last updated 5 months ago.

software singlecell visualization go transcriptomics

1.5 match 9 stars 4.95 score 7 scripts

eddelbuettel

RcppFastAD:'Rcpp' Bindings to 'FastAD' Auto-Differentiation

The header-only 'C++' template library 'FastAD' for automatic differentiation <https://github.com/JamesYang007/FastAD> is provided by this package, along with a few illustrative examples that can all be called from R.

Maintained by Dirk Eddelbuettel. Last updated 6 months ago.

cpp

1.7 match 10 stars 4.40 score 4 scripts

cran

FlexParamCurve:Tools to Fit Flexible Parametric Curves

Model selection tools and 'selfStart' functions to fit parametric curves in 'nls', 'nlsList' and 'nlme' frameworks.

Maintained by Stephen Oswald. Last updated 1 years ago.

3.6 match 1.90 score

cran

pmr:Probability Models for Ranking Data

Descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce models, distance-based models, and rank-ordered logit models) and visualization with multidimensional preference analysis for ranking data are provided. Current, only complete rankings are supported by this package.

Maintained by Paul H. Lee. Last updated 3 years ago.

4.5 match 1.48 score 1 dependents

cran

optionstrat:Utilizes the Black-Scholes Option Pricing Model to Perform Strategic Option Analysis and Plot Option Strategies

Utilizes the Black-Scholes-Merton option pricing model to calculate key option analytics and perform graphical analysis of various option strategies. Provides functions to calculate the option premium and option greeks of European-style options.

Maintained by John T. Buynak. Last updated 5 years ago.

3.2 match 2.00 score

objornstad

epimdr:Functions and Data for "Epidemics: Models and Data in R"

Functions, data sets and shiny apps for "Epidemics: Models and Data in R" by Ottar N. Bjornstad (ISBN 978-3-319-97487-3) <https://www.springer.com/gp/book/9783319974866>. The package contains functions to study the S(E)IR model, spatial and age-structured SIR models; time-series SIR and chain-binomial stochastic models; catalytic disease models; coupled map lattice models of spatial transmission and network models for social spread of infection. The package is also an advanced quantitative companion to the coursera Epidemics Massive Online Open Course <https://www.coursera.org/learn/epidemics>.

Maintained by Ottar N. Bjornstad. Last updated 5 years ago.

3.8 match 1.65 score 45 scripts

jagm03

kernstadapt:Adaptive Kernel Estimators for Point Process Intensities on Linear Networks

Adaptive estimation of the first-order intensity function of a spatio-temporal point process using kernels and variable bandwidths. The methodology used for estimation is presented in González and Moraga (2022). <doi:10.48550/arXiv.2208.12026>.

Maintained by Jonatan A González. Last updated 6 months ago.

1.1 match 6 stars 5.51 score 12 scripts

eliascarvalho

bnpa:Bayesian Networks & Path Analysis

This project aims to enable the method of Path Analysis to infer causalities from data. For this we propose a hybrid approach, which uses Bayesian network structure learning algorithms from data to create the input file for creation of a PA model. The process is performed in a semi-automatic way by our intermediate algorithm, allowing novice researchers to create and evaluate their own PA models from a data set. The references used for this project are: Koller, D., & Friedman, N. (2009). Probabilistic graphical models: principles and techniques. MIT press. <doi:10.1017/S0269888910000275>. Nagarajan, R., Scutari, M., & Lèbre, S. (2013). Bayesian networks in r. Springer, 122, 125-127. Scutari, M., & Denis, J. B. <doi:10.1007/978-1-4614-6446-4>. Scutari M (2010). Bayesian networks: with examples in R. Chapman and Hall/CRC. <doi:10.1201/b17065>. Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1 - 36. <doi:10.18637/jss.v048.i02>.

Maintained by Elias Carvalho. Last updated 6 years ago.

openjdk

3.6 match 1.66 score 46 scripts

triadsou

RcmdrPlugin.KMggplot2:R Commander Plug-in for Data Visualization with 'ggplot2'

A GUI front-end for 'ggplot2' supports Kaplan-Meier plot, histogram, Q-Q plot, box plot, errorbar plot, scatter plot, line chart, pie chart, bar chart, contour plot, and distribution plot.

Maintained by Triad sou.. Last updated 6 years ago.

1.9 match 3.18 score 8 scripts

nhejazi

nima:Nima Hejazi's R Toolbox

Miscellaneous R functions developed as collateral damage over the course of work in statistical and scientific computing for research. These include, for example, utilities that supplement existing idiosyncrasies of the R language, extend existing plotting functionality and aesthetics, help prepare data objects for imputation, and extend access to command line tools and systems-level information.

Maintained by Nima Hejazi. Last updated 5 years ago.

1.8 match 3.22 score 33 scripts

darwin-eu

TestGenerator:Integration Unit Tests for Pharmacoepidemiological Studies

Push a sample population for unit testing on data mapped to the Observational Medical Outcomes Partnership (OMOP) Common Data Model.

Maintained by Cesar Barboza. Last updated 4 months ago.

1.5 match 3.70 score 2 scripts

andremueller

colorpatch:Optimized Rendering of Fold Changes and Confidence Values

Shows color patches for encoding fold changes (e.g. log ratios) together with confidence values within a single diagram. This is especially useful for rendering gene expression data as well as other types of differential experiments. In addition to different rendering methods (ggplot extensions) functionality for perceptually optimizing color palettes are provided. Furthermore the package provides extension methods of the colorspace color-class in order to simplify the work with palettes (a.o. length, as.list, and append are supported).

Maintained by Andre Mueller. Last updated 8 years ago.

1.8 match 3.23 score 34 scripts

thomasp85

lime:Local Interpretable Model-Agnostic Explanations

When building complex models, it is often difficult to explain why the model should be trusted. While global measures such as accuracy are useful, they cannot be used for explaining why a model made a specific prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for explaining the outcome of black box models by fitting a local model around the point in question an perturbations of this point. The approach is described in more detail in the article by Ribeiro et al. (2016) <arXiv:1602.04938>.

Maintained by Emil Hvitfeldt. Last updated 3 years ago.

caret model-checking model-evaluation modeling cpp

0.5 match 485 stars 11.07 score 732 scripts 1 dependents

cran

BLModel:Black-Litterman Posterior Distribution

Posterior distribution in the Black-Litterman model is computed from a prior distribution given in the form of a time series of asset returns and a continuous distribution of views provided by the user as an external function.

Maintained by Andrzej Palczewski. Last updated 8 years ago.

5.4 match 1.00 score

matt-dray

coloratio:Assess Color Contrast Ratios for Accessibility

Tools to help choose accessible color combinations based on W3C specifications.

Maintained by Matt Dray. Last updated 4 years ago.

accessibility color contrast-ratio

1.7 match 8 stars 3.03 score 27 scripts

trinker

textclean:Text Cleaning Tools

Tools to clean and process text. Tools are geared at checking for substrings that are not optimal for analysis and replacing or removing them (normalizing) with more analysis friendly substrings (see Sproat, Black, Chen, Kumar, Ostendorf, & Richards (2001) <doi:10.1006/csla.2001.0169>) or extracting them into new variables. For example, emoticons are often used in text but not always easily handled by analysis algorithms. The replace_emoticon() function replaces emoticons with word equivalents.

Maintained by Tyler Rinker. Last updated 3 years ago.

data-munging emoticons regex text-analysis text-cleaning

0.5 match 248 stars 10.08 score 760 scripts 22 dependents

modeloriented

iBreakDown:Model Agnostic Instance Level Variable Attributions

Model agnostic tool for decomposition of predictions from black boxes. Supports additive attributions and attributions with interactions. The Break Down Table shows contributions of every variable to a final prediction. The Break Down Plot presents variable contributions in a concise graphical way. This package works for classification and regression models. It is an extension of the 'breakDown' package (Staniak and Biecek 2018) <doi:10.32614/RJ-2018-072>, with new and faster strategies for orderings. It supports interactions in explanations and has interactive visuals (implemented with 'D3.js' library). The methodology behind is described in the 'iBreakDown' article (Gosiewska and Biecek 2019) <arXiv:1903.11420> This package is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.

Maintained by Przemyslaw Biecek. Last updated 1 years ago.

breakdown iml interpretability shapley xai

0.5 match 84 stars 10.07 score 56 scripts 22 dependents

tconwell

bsTools:Create HTML Content with Bootstrap 5 Classes and Layouts

Functions are pre-configured to utilize Bootstrap 5 classes and HTML structures to create Bootstrap-styled HTML quickly and easily. Includes functions for creating common Bootstrap elements such as containers, rows, cols, navbars, etc. Intended to be used with the html5 package. Learn more at <https://getbootstrap.com/>.

Maintained by Timothy Conwell. Last updated 2 years ago.

1.8 match 1 stars 2.70 score 2 scripts

pbiecek

breakDown:Model Agnostic Explainers for Individual Predictions

Model agnostic tool for decomposition of predictions from black boxes. Break Down Table shows contributions of every variable to a final prediction. Break Down Plot presents variable contributions in a concise graphical way. This package work for binary classifiers and general regression models.

Maintained by Przemyslaw Biecek. Last updated 1 years ago.

data-science iml interpretability machine-learning visual-explanations xai

0.5 match 103 stars 8.90 score 91 scripts 2 dependents

marioangst

rayab:R package for AYAB compatible images

Functionality to create images suitable for two-color knitting via the AYAB (all yarns are beautiful) open source software/ hardware project from plots, text and images.

Maintained by Mario Angst. Last updated 3 months ago.

1.7 match 1 stars 2.70 score 5 scripts

bgreenwell

fastshap:Fast Approximate Shapley Values

Computes fast (relative to other implementations) approximate Shapley values for any supervised learning model. Shapley values help to explain the predictions from any black box model using ideas from game theory; see Strumbel and Kononenko (2014) <doi:10.1007/s10115-013-0679-x> for details.

Maintained by Brandon Greenwell. Last updated 1 years ago.

explainable-ai explainable-ml interpretable-machine-learning shapley shapley-values variable-importance xai cpp

0.5 match 118 stars 8.56 score 155 scripts 2 dependents

bioc

BubbleTree:BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality in somatic mosaicism using next generation sequencing data

CNV analysis in groups of tumor samples.

Maintained by Todd Creasy. Last updated 5 months ago.

copynumbervariation software sequencing coverage

1.1 match 3.95 score 15 scripts

modeloriented

survex:Explainable Machine Learning in Survival Analysis

Survival analysis models are commonly used in medicine and other areas. Many of them are too complex to be interpreted by human. Exploration and explanation is needed, but standard methods do not give a broad enough picture. 'survex' provides easy-to-apply methods for explaining survival models, both complex black-boxes and simpler statistical models. They include methods specific to survival analysis such as SurvSHAP(t) introduced in Krzyzinski et al., (2023) <doi:10.1016/j.knosys.2022.110234>, SurvLIME described in Kovalev et al., (2020) <doi:10.1016/j.knosys.2020.106164> as well as extensions of existing ones described in Biecek et al., (2021) <doi:10.1201/9780429027192>.

Maintained by Mikołaj Spytek. Last updated 9 months ago.

biostatistics brier-scores censored-data cox-model cox-regression explainable-ai explainable-machine-learning explainable-ml explanatory-model-analysis interpretable-machine-learning interpretable-ml machine-learning probabilistic-machine-learning shap survival-analysis time-to-event variable-importance xai

0.5 match 110 stars 8.40 score 114 scripts

sleire

etrm:Energy Trading and Risk Management

Provides a collection of functions to perform core tasks within Energy Trading and Risk Management (ETRM). Calculation of maximum smoothness forward price curves for electricity and natural gas contracts with flow delivery, as presented in F. E. Benth, S. Koekebakker, and F. Ollmar (2007) <doi:10.3905/jod.2007.694791> and F. E. Benth, J. S. Benth, and S. Koekebakker (2008) <doi:10.1142/6811>. Portfolio insurance trading strategies for price risk management in the forward market, see F. Black (1976) <doi:10.1016/0304-405X(76)90024-6>, T. Bjork (2009) <https://EconPapers.repec.org/RePEc:oxp:obooks:9780199574742>, F. Black and R. W. Jones (1987) <doi:10.3905/jpm.1987.409131> and H. E. Leland (1980) <http://www.jstor.org/stable/2327419>.

Maintained by Anders D. Sleire. Last updated 2 years ago.

commodities energy-trading risk-management trading-strategies

0.8 match 33 stars 5.52 score 10 scripts

rstudio

reactlog:Reactivity Visualizer for 'shiny'

Building interactive web applications with R is incredibly easy with 'shiny'. Behind the scenes, 'shiny' builds a reactive graph that can quickly become intertwined and difficult to debug. 'reactlog' (Schloerke 2019) <doi:10.5281/zenodo.2591517> provides a visual insight into that black box of 'shiny' reactivity by constructing a directed dependency graph of the application's reactive state at any time point in a reactive recording.

Maintained by Barret Schloerke. Last updated 2 years ago.

0.5 match 125 stars 8.15 score 263 scripts

karchjd

TauStar:Efficient Computation and Testing of the Bergsma-Dassios Sign Covariance

Computes the t* statistic corresponding to the tau* population coefficient introduced by Bergsma and Dassios (2014) <DOI:10.3150/13-BEJ514> and does so in O(n^2) time following the algorithm of Heller and Heller (2016) <DOI:10.48550/arXiv.1605.08732> building off of the work of Weihs, Drton, and Leung (2016) <DOI:10.1007/s00180-015-0639-x>. Also allows for independence testing using the asymptotic distribution of t* as described by Nandy, Weihs, and Drton (2016) <DOI:10.1214/16-EJS1166>.

Maintained by Julian D. Karch. Last updated 3 months ago.

openblas cpp

1.6 match 2 stars 2.60 score 40 scripts

modeloriented

modelStudio:Interactive Studio for Explanatory Model Analysis

Automate the explanatory analysis of machine learning predictive models. Generate advanced interactive model explanations in the form of a serverless HTML site with only one line of code. This tool is model-agnostic, therefore compatible with most of the black-box predictive models and frameworks. The main function computes various (instance and model-level) explanations and produces a customisable dashboard, which consists of multiple panels for plots with their short descriptions. It is possible to easily save the dashboard and share it with others. 'modelStudio' facilitates the process of Interactive Explanatory Model Analysis introduced in Baniecki et al. (2023) <doi:10.1007/s10618-023-00924-w>.

Maintained by Hubert Baniecki. Last updated 2 years ago.

ai explainable explainable-ai explainable-machine-learning explanatory-model-analysis human iml interactive interactivity interpretability interpretable interpretable-machine-learning learning machine model model-visualization visualization xai

0.5 match 330 stars 7.92 score 56 scripts

modeloriented

DALEXtra:Extension for 'DALEX' Package

Provides wrapper of various machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the interpretable machine learning, there are more and more new ideas for explaining black-box models, that are implemented in 'R'. 'DALEXtra' creates 'DALEX' Biecek (2018) <arXiv:1806.08915> explainer for many type of models including those created using 'python' 'scikit-learn' and 'keras' libraries, and 'java' 'h2o' library. Important part of the package is Champion-Challenger analysis and innovative approach to model performance across subsets of test data presented in Funnel Plot.

Maintained by Szymon Maksymiuk. Last updated 2 years ago.

extension-for-dalex-package

0.5 match 67 stars 7.71 score 400 scripts 1 dependents

mlr-org

mlr3hyperband:Hyperband for 'mlr3'

Successive Halving (Jamieson and Talwalkar (2016) <doi:10.48550/arXiv.1502.07943>) and Hyperband (Li et al. 2018 <doi:10.48550/arXiv.1603.06560>) optimization algorithm for the mlr3 ecosystem. The implementation in mlr3hyperband features improved scheduling and parallelizes the evaluation of configurations. The package includes tuners for hyperparameter optimization in mlr3tuning and optimizers for black-box optimization in bbotk.

Maintained by Marc Becker. Last updated 9 months ago.

automl bbotk hyperband hyperparameter-tuning machine-learning mlr3 optimization tune tuning

0.5 match 18 stars 7.48 score 44 scripts 3 dependents

bdhitt

binGroup2:Identification and Estimation using Group Testing

Methods for the group testing identification problem: 1) Operating characteristics (e.g., expected number of tests) for commonly used hierarchical and array-based algorithms, and 2) Optimal testing configurations for these same algorithms. Methods for the group testing estimation problem: 1) Estimation and inference procedures for an overall prevalence, and 2) Regression modeling for commonly used hierarchical and array-based algorithms.

Maintained by Brianna Hitt. Last updated 1 years ago.

openblas cpp

1.5 match 2.48 score 3 scripts 1 dependents

cran

hbal:Hierarchically Regularized Entropy Balancing

Implements hierarchically regularized entropy balancing proposed by Xu and Yang (2022) <doi:10.1017/pan.2022.12>. The method adjusts the covariate distributions of the control group to match those of the treatment group. 'hbal' automatically expands the covariate space to include higher order terms and uses cross-validation to select variable penalties for the balancing conditions.

Maintained by Yiqing Xu. Last updated 1 years ago.

cpp

3.8 match 1.00 score

modeloriented

shapper:Wrapper of Python Library 'shap'

Provides SHAP explanations of machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the Interpretable Machine Learning, there are more and more new ideas for explaining black-box models. One of the best known method for local explanations is SHapley Additive exPlanations (SHAP) introduced by Lundberg, S., et al., (2016) <arXiv:1705.07874> The SHAP method is used to calculate influences of variables on the particular observation. This method is based on Shapley values, a technique used in game theory. The R package 'shapper' is a port of the Python library 'shap'.

Maintained by Szymon Maksymiuk. Last updated 2 years ago.

0.5 match 58 stars 7.31 score 59 scripts

tripartio

ale:Interpretable Machine Learning and Statistical Inference with Accumulated Local Effects (ALE)

Accumulated Local Effects (ALE) were initially developed as a model-agnostic approach for global explanations of the results of black-box machine learning algorithms. ALE has a key advantage over other approaches like partial dependency plots (PDP) and SHapley Additive exPlanations (SHAP): its values represent a clean functional decomposition of the model. As such, ALE values are not affected by the presence or absence of interactions among variables in a mode. Moreover, its computation is relatively rapid. This package reimplements the algorithms for calculating ALE data and develops highly interpretable visualizations for plotting these ALE values. It also extends the original ALE concept to add bootstrap-based confidence intervals and ALE-based statistics that can be used for statistical inference. For more details, see Okoli, Chitu. 2023. “Statistical Inference Using Machine Learning and Classical Techniques Based on Accumulated Local Effects (ALE).” arXiv. <arXiv:2310.09877>. <doi:10.48550/arXiv.2310.09877>.

Maintained by Chitu Okoli. Last updated 26 days ago.

0.5 match 4 stars 6.41 score 27 scripts

matildabrown

rWCVP:Generating Summaries, Reports and Plots from the World Checklist of Vascular Plants

A companion to the World Checklist of Vascular Plants (WCVP). It includes functions to generate maps and species lists, as well as match names to the WCVP. For more details and to cite the package, see: Brown M.J.M., Walker B.E., Black N., Govaerts R., Ondo I., Turner R., Nic Lughadha E. (in press). "rWCVP: A companion R package to the World Checklist of Vascular Plants". New Phytologist.

Maintained by Matilda Brown. Last updated 1 years ago.

0.5 match 22 stars 6.17 score 45 scripts 1 dependents

gabrielelubatti

SCOPRO:Score Projection Between in 'Vivo' and in 'Vitro' Datasets

Assigns a score projection from 0 to 1 between a given in 'vivo' stage and each single cluster from an in 'vitro' dataset. The score is assigned based on the the fraction of specific markers of the in 'vivo' stage that are conserved in the in 'vitro' clusters <https://github.com/ScialdoneLab>.

Maintained by Gabriele Lubatti. Last updated 3 years ago.

software

1.2 match 2.70 score 3 scripts

brentkaplan

beezdemand:Behavioral Economic Easy Demand

Facilitates many of the analyses performed in studies of behavioral economic demand. The package supports commonly-used options for modeling operant demand including (1) data screening proposed by Stein, Koffarnus, Snider, Quisenberry, & Bickel (2015; <doi:10.1037/pha0000020>), (2) fitting models of demand such as linear (Hursh, Raslear, Bauman, & Black, 1989, <doi:10.1007/978-94-009-2470-3_22>), exponential (Hursh & Silberberg, 2008, <doi:10.1037/0033-295X.115.1.186>) and modified exponential (Koffarnus, Franck, Stein, & Bickel, 2015, <doi:10.1037/pha0000045>), and (3) calculating numerous measures relevant to applied behavioral economists (Intensity, Pmax, Omax). Also supports plotting and comparing data.

Maintained by Brent Kaplan. Last updated 7 months ago.

0.5 match 15 stars 6.12 score 29 scripts 1 dependents

mbinois

GPareto:Gaussian Processes for Pareto Front Estimation and Optimization

Gaussian process regression models, a.k.a. Kriging models, are applied to global multi-objective optimization of black-box functions. Multi-objective Expected Improvement and Step-wise Uncertainty Reduction sequential infill criteria are available. A quantification of uncertainty on Pareto fronts is provided using conditional simulations.

Maintained by Mickael Binois. Last updated 1 years ago.

cpp

0.5 match 16 stars 5.96 score 38 scripts 1 dependents

mps9506

mpsTemplates:Templates for Me

Provides opinionated ggplot2 themes and other templates for my own use.

Maintained by Michael Schramm. Last updated 2 years ago.

1.8 match 1.70 score 4 scripts

cmmr

fillpattern:Patterned Fills for 'ggplot2' and 'grid' Graphics

Adds distinctive yet unobtrusive geometric patterns where solid color fills are normally used. Patterned figures look just as professional when viewed by colorblind readers or when printed in black and white. The dozen included patterns can be customized in terms of scale, rotation, color, fill, line type, and line width. Compatible with the 'ggplot2' package as well as 'grid' graphics.

Maintained by Daniel P. Smith. Last updated 9 months ago.

0.5 match 7 stars 5.51 score 13 scripts 7 dependents

riatelab

tanaka:Design Shaded Contour Lines (or Tanaka) Maps

The Tanaka method enhances the representation of topography on a map using shaded contour lines. In this simplified implementation of the method, north-west white contours represent illuminated topography and south-east black contours represent shaded topography. See Tanaka (1950) <doi:10.2307/211219>.

Maintained by Timothée Giraud. Last updated 1 years ago.

map spatial tanaka

0.5 match 79 stars 5.40 score 21 scripts 1 dependents

jwboys26

KoulMde:Koul's Minimum Distance Estimation in Regression and Image Segmentation Problems

Many methods are developed to deal with two major statistical problems: image segmentation and nonparametric estimation in various regression models. Image segmentation is nowadays gaining a lot of attention from various scientific subfields. Especially, image segmentation has been popular in medical research such as magnetic resonance imaging (MRI) analysis. When a patient suffers from some brain diseases such as dementia and Parkinson's disease, those diseases can be easily diagnosed in brain MRI: the area affected by those diseases is brightly expressed in MRI, which is called a white lesion. For the purpose of medical research, locating and segment those white lesions in MRI is a critical issue; it can be done manually. However, manual segmentation is very expensive in that it is error-prone and demands a huge amount of time. Therefore, supervised machine learning has emerged as an alternative solution. Despite its powerful performance in a classification problem such as hand-written digits, supervised machine learning has not shown the same satisfactory result in MRI analysis. Setting aside all issues of the supervised machine learning, it exposed a critical problem when employed for MRI analysis: it requires time-consuming data labeling. Thus, there is a strong demand for an unsupervised approach, and this package - based on Hira L. Koul (1986) <DOI:10.1214/aos/1176350059> - proposes an efficient method for simple image segmentation - here, "simple" means that an image is black-and-white - which can easily be applied to MRI analysis. This package includes a function GetSegImage(): when a black-and-white image is given as an input, GetSegImage() separates an area of white pixels - which corresponds to a white lesion in MRI - from the given image. For the second problem, consider linear regression model and autoregressive model of order q where errors in the linear regression model and innovations in the autoregression model are independent and symmetrically distributed. Hira L. Koul (1986) <DOI:10.1214/aos/1176350059> proposed a nonparametric minimum distance estimation method by minimizing L2-type distance between certain weighted residual empirical processes. He also proposed a simpler version of the loss function by using symmetry of the integrating measure in the distance. Kim (2018) <DOI:10.1080/00949655.2017.1392527> proposed a fast computational method which enables practitioners to compute the minimum distance estimator of the vector of general multiple regression parameters for several integrating measures. This package contains three functions: KoulLrMde(), KoulArMde(), and Koul2StageMde(). The former two provide minimum distance estimators for linear regression model and autoregression model, respectively, where both are based on Koul's method. These two functions take much less time for the computation than those based on parametric minimum distance estimation methods. Koul2StageMde() provides estimators for regression and autoregressive coefficients of linear regression model with autoregressive errors through minimum distant method of two stages. The new version is written in Rcpp and dramatically reduces computational time.

Maintained by Jiwoong Kim. Last updated 5 years ago.

openblas cpp

2.6 match 1.00 score 3 scripts

leonawicz

imgpalr:Create Color Palettes from Images

Provides ability to create color palettes from image files. It offers control over the type of color palette to derive from an image (qualitative, sequential or divergent) and other palette properties. Quantiles of an image color distribution can be trimmed. Near-black or near-white colors can be trimmed in RGB color space independent of trimming brightness or saturation distributions in HSV color space. Creating sequential palettes also offers control over the order of HSV color dimensions to sort by. This package differs from other related packages like 'RImagePalette' in approaches to quantizing and extracting colors in images to assemble color palettes and the level of user control over palettes construction.

Maintained by Matthew Leonawicz. Last updated 6 months ago.

color color-palette image-classification image-processing

0.5 match 52 stars 4.65 score 17 scripts

cran

OptionPricing:Option Pricing with Efficient Simulation Algorithms

Efficient Monte Carlo Algorithms for the price and the sensitivities of Asian and European Options under Geometric Brownian Motion.

Maintained by Wolfgang Hormann. Last updated 2 years ago.

1.8 match 2 stars 1.30 score

ilundberg

gapclosing:Estimate Gaps Under an Intervention

Provides functions to estimate the disparities across categories (e.g. Black and white) that persists if a treatment variable (e.g. college) is equalized. Makes estimates by treatment modeling, outcome modeling, and doubly-robust augmented inverse probability weighting estimation, with standard errors calculated by a nonparametric bootstrap. Cross-fitting is supported. Survey weights are supported for point estimation but not for standard error estimation; those applying this package with complex survey samples should consult the data distributor to select an appropriate approach for standard error construction, which may involve calling the functions repeatedly for many sets of replicate weights provided by the data distributor. The methods in this package are described in Lundberg (2021) <doi:10.31235/osf.io/gx4y3>.

Maintained by Ian Lundberg. Last updated 3 months ago.

0.5 match 6 stars 4.48 score 8 scripts

cran

LSMonteCarlo:American options pricing with Least Squares Monte Carlo method

The package compiles functions for calculating prices of American put options with Least Squares Monte Carlo method. The option types are plain vanilla American put, Asian American put, and Quanto American put. The pricing algorithms include variance reduction techniques such as Antithetic Variates and Control Variates. Additional functions are given to derive "price surfaces" at different volatilities and strikes, create 3-D plots, quickly generate Geometric Brownian motion, and calculate prices of European options with Black & Scholes analytical solution.

Maintained by Mikhail A. Beketov. Last updated 11 years ago.

2.3 match 1 stars 1.00 score

cran

pcalls:Pricing of Different Types of Call

Compute the price of different types of call using different methods. The types available are Vanilla European Calls, Vanilla American Calls and American Digital Calls. Available methods are Montecarlo Simulation, Montecarlo Simulation with Antithetic Variates, Black-Scholes and the Binary Tree.

Maintained by Elia Degiorgi. Last updated 5 years ago.

2.2 match 1.00 score

digi-vub

image.binarization:Binarize Images for Enhancing Optical Character Recognition

Improve optical character recognition by binarizing images. The package focuses primarily on local adaptive thresholding algorithms. In English, this means that it has the ability to turn a color or gray scale image into a black and white image. This is particularly useful as a preprocessing step for optical character recognition or handwritten text recognition.

Maintained by Jan Wijffels. Last updated 3 years ago.

cpp

0.5 match 21 stars 4.17 score 14 scripts

zumbov2

colorizer:Colorize Old Images Using the 'DeOldify' Image Colorization API

Call the 'DeOldify' <https://github.com/jantic/DeOldify> image colorization API on 'DeepAI'<https://deepai.org/machine-learning-model/colorizer> to colorize black and white images.

Maintained by David Zumbach. Last updated 4 years ago.

colorization deoldify image

0.5 match 21 stars 4.02 score 3 scripts

mb706

mlrintermbo:Model-Based Optimization for 'mlr3' Through 'mlrMBO'

The 'mlrMBO' package can ordinarily not be used for optimization within 'mlr3', because of incompatibilities of their respective class systems. 'mlrintermbo' offers a compatibility interface that provides 'mlrMBO' as an 'mlr3tuning' 'Tuner' object, for tuning of machine learning algorithms within 'mlr3', as well as a 'bbotk' 'Optimizer' object for optimization of general objective functions using the 'bbotk' black box optimization framework. The control parameters of 'mlrMBO' are faithfully reproduced as a 'paradox' 'ParamSet'.

Maintained by Martin Binder. Last updated 5 months ago.

0.5 match 4 stars 4.08 score 12 scripts

storopoli

FactorAssumptions:Set of Assumptions for Factor and Principal Component Analysis

Tests for Kaiser-Meyer-Olkin (KMO) and communalities in a dataset. It provides a final sample by removing variables in a iterable manner while keeping account of the variables that were removed in each step. It follows the best practices and assumptions according to Hair, Black, Babin & Anderson (2018, ISBN:9781473756540).

Maintained by Jose Storopoli. Last updated 3 years ago.

0.5 match 2 stars 4.00 score 7 scripts

forestry-labs

distillML:Model Distillation and Interpretability Methods for Machine Learning Models

Provides several methods for model distillation and interpretability for general black box machine learning models and treatment effect estimation methods. For details on the algorithms implemented, see <https://forestry-labs.github.io/distillML/index.html> Brian Cho, Theo F. Saarinen, Jasjeet S. Sekhon, Simon Walter.

Maintained by Theo Saarinen. Last updated 2 years ago.

bart distillation-model explainable-machine-learning explainable-ml interpretability interpretable-machine-learning machine-learning model random-forest xgboost

0.5 match 7 stars 3.92 score 12 scripts

dapley

ALEPlot:Accumulated Local Effects (ALE) Plots and Partial Dependence (PD) Plots

Visualizes the main effects of individual predictor variables and their second-order interaction effects in black-box supervised learning models. The package creates either Accumulated Local Effects (ALE) plots and/or Partial Dependence (PD) plots, given a fitted supervised learning model.

Maintained by Dan Apley. Last updated 7 years ago.

0.5 match 5 stars 3.85 score 58 scripts

paulesantos

ppendemic:A Glimpse at the Diversity of Peru's Endemic Plants

Introducing a novel and updated database showcasing Peru's endemic plants. This meticulously compiled and revised botanical collection encompasses a remarkable assemblage of over 7,249 distinct species. The data for this resource was sourced from the work of Govaerts, R., Nic Lughadha, E., Black, N. et al., titled 'The World Checklist of Vascular Plants: A continuously updated resource for exploring global plant diversity', published in Sci Data 8, 215 (2021) <doi:10.1038/s41597-021-00997-6>.

Maintained by Paul E. Santos Andrade. Last updated 8 months ago.

endemic peru plants

0.5 match 8 stars 3.90 score 8 scripts

meenakshi-kushwaha

mmaqshiny:Explore Air Quality Mobile-Monitoring Data

Mobile-monitoring or sensors on a mobile platform, is an increasingly popular approach to measure high-resolution pollution data at the street level. Coupled with location data, spatial visualization of air-quality parameters helps detect localized areas of high air pollution, also called hotspots. In this approach, portable sensors are mounted on a vehicle and driven on predetermined routes to collect high frequency data (1 Hz). 'mmaqshiny' is for analysing, visualizing and spatial mapping of high-resolution air-quality data collected by specific devices installed on a moving platform. 1 Hz data of PM2.5 (mass concentrations of particulate matter with size less than 2.5 microns), Black carbon mass concentrations (BC), ultra-fine particle number concentrations, carbon dioxide along with GPS coordinates and relative humidity (RH) data collected by popular portable instruments (TSI DustTrak-8530, Aethlabs microAeth-AE51, TSI CPC3007, LICOR Li-830, Garmin GPSMAP 64s, Omega USB RH probe respectively). It incorporates device specific cleaning and correction algorithms. RH correction is applied to DustTrak PM2.5 following the Chakrabarti et al., (2004) <doi:10.1016/j.atmosenv.2004.03.007>. Provision is given to add linear regression coefficients for correcting the PM2.5 data (if required). BC data will be cleaned for the vibration generated noise, by adopting the statistical procedure as explained in Apte et al., (2011) <doi:10.1016/j.atmosenv.2011.05.028>, followed by a loading correction as suggested by Ban-Weiss et al., (2009) <doi:10.1021/es8021039>. For the number concentration data, provision is given for dilution correction factor (if a diluter is used with CPC3007; default value is 1). The package joins the raw, cleaned and corrected data from the above said instruments and outputs as a downloadable csv file.

Maintained by Adithi R. Upadhya. Last updated 3 years ago.

0.5 match 5 stars 3.70 score 4 scripts

cran

sonar:Fundamental Formulas for Sonar

Formulas for calculating sound velocity, water pressure, depth, density, absorption and sonar equations.

Maintained by Jose Gama. Last updated 9 years ago.

1.8 match 1.00 score

cran

ashapesampler:Generating Alpha Shapes

Understanding morphological variation is an important task in many applications. Recent studies in computational biology have focused on developing computational tools for the task of sub-image selection which aims at identifying structural features that best describe the variation between classes of shapes. A major part in assessing the utility of these approaches is to demonstrate their performance on both simulated and real datasets. However, when creating a model for shape statistics, real data can be difficult to access and the sample sizes for these data are often small due to them being expensive to collect. Meanwhile, the landscape of current shape simulation methods has been mostly limited to approaches that use black-box inference---making it difficult to systematically assess the power and calibration of sub-image models. In this R package, we introduce the alpha-shape sampler: a probabilistic framework for simulating realistic 2D and 3D shapes based on probability distributions which can be learned from real data or explicitly stated by the user. The 'ashapesampler' package supports two mechanisms for sampling shapes in two and three dimensions. The first, empirically sampling based on an existing data set, was highlighted in the original main text of the paper. The second, probabilistic sampling from a known distribution, is the computational implementation of the theory derived in that paper. Work based on Winn-Nunez et al. (2024) <doi:10.1101/2024.01.09.574919>.

Maintained by Emily Winn-Nunez. Last updated 1 years ago.

0.5 match 3.30 score 8 scripts

vpicheny

GPGame:Solving Complex Game Problems using Gaussian Processes

Sequential strategies for finding a game equilibrium are proposed in a black-box setting (expensive pay-off evaluations, no derivatives). The algorithm handles noiseless or noisy evaluations. Two acquisition functions are available. Graphical outputs can be generated automatically. V. Picheny, M. Binois, A. Habbal (2018) <doi:10.1007/s10898-018-0688-0>. M. Binois, V. Picheny, P. Taillandier, A. Habbal (2020) <arXiv:1902.06565v2>.

Maintained by Victor Picheny. Last updated 3 years ago.

cpp

0.5 match 2.70 score

cran

IADT:Interaction Difference Test for Prediction Models

Provides functions to conduct a model-agnostic asymptotic hypothesis test for the identification of interaction effects in black-box machine learning models. The null hypothesis assumes that a given set of covariates does not contribute to interaction effects in the prediction model. The test statistic is based on the difference of variances of partial dependence functions (Friedman (2008) <doi:10.1214/07-AOAS148> and Welchowski (2022) <doi:10.1007/s13253-021-00479-7>) with respect to the original black-box predictions and the predictions under the null hypothesis. The hypothesis test can be applied to any black-box prediction model, and the null hypothesis of the test can be flexibly specified according to the research question of interest. Furthermore, the test is computationally fast to apply as the null distribution does not require resampling or refitting black-box prediction models.

Maintained by Thomas Welchowski. Last updated 10 months ago.

1.0 match 1 stars 1.00 score

anuragagrawaal

roptions:Option Strategies and Valuation

Collection of tools to develop options strategies, value option contracts using the Black-Scholes-Merten option pricing model and calculate the option Greeks. Hull, John C. "Options, Futures, and Other Derivatives" (1997, ISBN:0-13-601589-1). Fischer Black, Myron Scholes (1973) "The Pricing of Options and Corporate Liabilities" <doi:10.1086/260062>.

Maintained by Anurag Agrawal. Last updated 5 years ago.

0.8 match 1.00 score

shangkun-wang

OSFD:Output Space-Filling Design

Methods to generate a design in the input space that sequentially fills the output space of a black-box function. The output space-filling designs are helpful in inverse design or feature-based modeling problems. See Wang, Shangkun, Adam P. Generale, Surya R. Kalidindi, and V. Roshan Joseph. (2024), Sequential designs for filling output spaces, Technometrics, 66, 65–76. for details. This work is supported by U.S. National Foundation grant CMMI-1921646.

Maintained by Shangkun Wang. Last updated 13 days ago.

openblas cpp

0.5 match 1.30 score

cran

RMPSH:Recursive Modified Pattern Search on Hyper-Rectangle

Optimization of any Black-Box/Non-Convex Function on Hyper-Rectangular Parameter Space. It uses a Variation of Pattern Search Technique. Described in the paper : Das (2016) <arXiv:1604.08616> .

Maintained by Priyam Das. Last updated 5 years ago.

cpp

0.5 match 1.00 score 4 scripts

simonmak

atmopt:Analysis-of-Marginal-Tail-Means

Provides functions for implementing the Analysis-of-marginal-Tail-Means (ATM) method, a robust optimization method for discrete black-box optimization. Technical details can be found in Mak and Wu (2018+) <arXiv:1712.03589>. This work was supported by USARO grant W911NF-17-1-0007.

Maintained by Simon Mak. Last updated 6 years ago.

0.5 match 1.00 score 7 scripts

colposerickg

CPoptim:Convex Partition Optimisation

Convex Partition is a black-box optimisation algorithm for single objective real-parameters functions. The basic principle is to progressively estimate and exploit a regression tree similar to a CART (Classification and Regression Tree) of the objective function. For more details see 'de Paz' (2024) <doi:10.1007/978-3-031-62836-8_3> and 'Loh' (2011) <doi:10.1002/widm.8> .

Maintained by Erick G.G. de Paz. Last updated 8 months ago.

0.5 match 1.00 score 1 scripts

vroshanjoseph

MOFAT:Maximum One-Factor-at-a-Time Designs

Identifying important factors from a large number of potentially important factors of a highly nonlinear and computationally expensive black box model is a difficult problem. Xiao, Joseph, and Ray (2022) <doi:10.1080/00401706.2022.2141897> proposed Maximum One-Factor-at-a-Time (MOFAT) designs for doing this. A MOFAT design can be viewed as an improvement to the random one-factor-at-a-time (OFAT) design proposed by Morris (1991) <doi:10.1080/00401706.1991.10484804>. The improvement is achieved by exploiting the connection between Morris screening designs and Monte Carlo-based Sobol' designs, and optimizing the design using a space-filling criterion. This work is supported by a U.S. National Science Foundation (NSF) grant CMMI-1921646 <https://www.nsf.gov/awardsearch/showAward?AWD_ID=1921646>.

Maintained by V. Roshan Joseph. Last updated 2 years ago.

0.5 match 1.00 score

cran

FWRGB:Fresh Weight Determination from Visual Image of the Plant

Fresh biomass determination is the key to evaluating crop genotypes' response to diverse input and stress conditions and forms the basis for calculating net primary production. However, as conventional phenotyping approaches for measuring fresh biomass is time-consuming, laborious and destructive, image-based phenotyping methods are being widely used now. In the image-based approach, the fresh weight of the above-ground part of the plant depends on the projected area. For determining the projected area, the visual image of the plant is converted into the grayscale image by simply averaging the Red(R), Green (G) and Blue (B) pixel values. Grayscale image is then converted into a binary image using Otsu’s thresholding method Otsu, N. (1979) <doi:10.1109/TSMC.1979.4310076> to separate plant area from the background (image segmentation). The segmentation process was accomplished by selecting the pixels with values over the threshold value belonging to the plant region and other pixels to the background region. The resulting binary image consists of white and black pixels representing the plant and background regions. Finally, the number of pixels inside the plant region was counted and converted to square centimetres (cm2) using the reference object (any object whose actual area is known previously) to get the projected area. After that, the projected area is used as input to the machine learning model (Linear Model, Artificial Neural Network, and Support Vector Regression) to determine the plant's fresh weight.

Maintained by Tanuj Misra. Last updated 3 years ago.

0.5 match 1.00 score