Showing 30 of total 30 results (show query)
tidymodels
infer:Tidy Statistical Inference
The objective of this package is to perform inference using an expressive statistical grammar that coheres with the tidy design framework.
Maintained by Simon Couch. Last updated 6 months ago.
736 stars 15.75 score 3.5k scripts 18 dependents
r-lib
generics:Common S3 Generics not Provided by Base R Methods Related to Model Fitting
In order to reduce potential package dependencies and conflicts, generics provides a number of commonly used S3 generics.
Maintained by Hadley Wickham. Last updated 1 years ago.
61 stars 14.00 score 131 scripts 9.8k dependents
mitchelloharawild
distributional:Vectorised Probability Distributions
Vectorised distribution objects with tools for manipulating, visualising, and using probability distributions. Designed to allow model prediction outputs to return distributions rather than their parameters, allowing users to directly interact with predictive distributions in a data-oriented workflow. In addition to providing generic replacements for p/d/q/r functions, other useful statistics can be computed including means, variances, intervals, and highest density regions.
Maintained by Mitchell OHara-Wild. Last updated 4 days ago.
probability-distributionstatisticsvctrs
100 stars 13.54 score 744 scripts 388 dependents
inlabru-org
inlabru:Bayesian Latent Gaussian Modelling using INLA and Extensions
Facilitates spatial and general latent Gaussian modeling using integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>). Additionally, extends the GAM-like model class to more general nonlinear predictor expressions, and implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. Model components are specified with general inputs and mapping methods to the latent variables, and the predictors are specified via general R expressions, with separate expressions for each observation likelihood model in multi-likelihood models. A prediction method based on fast Monte Carlo sampling allows posterior prediction of general expressions of the latent variables. Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) <doi:10.1111/2041-210X.13168>.
Maintained by Finn Lindgren. Last updated 3 days ago.
96 stars 12.59 score 832 scripts 6 dependents
tidyverts
fabletools:Core Tools for Packages in the 'fable' Framework
Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.
Maintained by Mitchell OHara-Wild. Last updated 2 months ago.
91 stars 12.18 score 396 scripts 18 dependents
epiverse-trace
epiparameter:Classes and Helper Functions for Working with Epidemiological Parameters
Classes and helper functions for loading, extracting, converting, manipulating, plotting and aggregating epidemiological parameters for infectious diseases. Epidemiological parameters extracted from the literature are loaded from the 'epiparameterDB' R package.
Maintained by Joshua W. Lambert. Last updated 2 months ago.
data-accessdata-packageepidemiologyepiverseprobability-distribution
34 stars 9.82 score 102 scripts 1 dependents
hauselin
ollamar:'Ollama' Language Models
An interface to easily run local language models with 'Ollama' <https://ollama.com> server and API endpoints (see <https://github.com/ollama/ollama/blob/main/docs/api.md> for details). It lets you run open-source large language models locally on your machine.
Maintained by Hause Lin. Last updated 7 days ago.
89 stars 9.32 score 74 scripts 5 dependents
genentech
psborrow2:Bayesian Dynamic Borrowing Analysis and Simulation
Bayesian dynamic borrowing is an approach to incorporating external data to supplement a randomized, controlled trial analysis in which external data are incorporated in a dynamic way (e.g., based on similarity of outcomes); see Viele 2013 <doi:10.1002/pst.1589> for an overview. This package implements the hierarchical commensurate prior approach to dynamic borrowing as described in Hobbes 2011 <doi:10.1111/j.1541-0420.2011.01564.x>. There are three main functionalities. First, 'psborrow2' provides a user-friendly interface for applying dynamic borrowing on the study results handles the Markov Chain Monte Carlo sampling on behalf of the user. Second, 'psborrow2' provides a simulation framework to compare different borrowing parameters (e.g. full borrowing, no borrowing, dynamic borrowing) and other trial and borrowing characteristics (e.g. sample size, covariates) in a unified way. Third, 'psborrow2' provides a set of functions to generate data for simulation studies, and also allows the user to specify their own data generation process. This package is designed to use the sampling functions from 'cmdstanr' which can be installed from <https://stan-dev.r-universe.dev>.
Maintained by Matt Secrest. Last updated 2 months ago.
bayesian-dynamic-borrowingpsborrow2simulation-study
18 stars 7.87 score 16 scripts
bayesiandemography
bage:Bayesian Estimation and Forecasting of Age-Specific Rates
Fast Bayesian estimation and forecasting of age-specific rates, probabilities, and means, based on 'Template Model Builder'.
Maintained by John Bryant. Last updated 14 days ago.
3 stars 7.41 score 39 scripts
hedgehogqa
hedgehog:Property-Based Testing
Hedgehog will eat all your bugs. 'Hedgehog' is a property-based testing package in the spirit of 'QuickCheck'. With 'Hedgehog', one can test properties of their programs against randomly generated input, providing far superior test coverage compared to unit testing. One of the key benefits of 'Hedgehog' is integrated shrinking of counterexamples, which allows one to quickly find the cause of bugs, given salient examples when incorrect behaviour occurs.
Maintained by Huw Campbell. Last updated 4 years ago.
56 stars 7.33 score 63 scripts 1 dependents
robjhyndman
vital:Tidy Analysis Tools for Mortality, Fertility, Migration and Population Data
Analysing vital statistics based on tools consistent with the tidyverse. Tools are provided for data visualization, life table calculations, computing net migration numbers, Lee-Carter modelling; functional data modelling and forecasting.
Maintained by Rob Hyndman. Last updated 4 days ago.
28 stars 7.20 score 18 scripts
ykang
gratis:Generating Time Series with Diverse and Controllable Characteristics
Generates synthetic time series based on various univariate time series models including MAR and ARIMA processes. Kang, Y., Hyndman, R.J., Li, F.(2020) <doi:10.1002/sam.11461>.
Maintained by Feng Li. Last updated 12 months ago.
data-generationmixture-autoregressivestatistical-computingtime-series
76 stars 6.98 score 25 scripts
statisfactions
simpr:Flexible 'Tidyverse'-Friendly Simulations
A general, 'tidyverse'-friendly framework for simulation studies, design analysis, and power analysis. Specify data generation, define varying parameters, generate data, fit models, and tidy model results in a single pipeline, without needing loops or custom functions.
Maintained by Ethan Brown. Last updated 9 months ago.
43 stars 6.89 score 30 scripts
sachaepskamp
psychonetrics:Structural Equation Modeling and Confirmatory Network Analysis
Multi-group (dynamical) structural equation models in combination with confirmatory network models from cross-sectional, time-series and panel data <doi:10.31234/osf.io/8ha93>. Allows for confirmatory testing and fit as well as exploratory model search.
Maintained by Sacha Epskamp. Last updated 4 days ago.
51 stars 6.88 score 41 scripts 1 dependents
dusadrian
QCA:Qualitative Comparative Analysis
An extensive set of functions to perform Qualitative Comparative Analysis: crisp sets ('csQCA'), temporal ('tQCA'), multi-value ('mvQCA') and fuzzy sets ('fsQCA'), using a GUI - graphical user interface. 'QCA' is a methodology that bridges the qualitative and quantitative divide in social science research. It uses a Boolean minimization algorithm, resulting in a minimal causal configuration associated with a given phenomenon.
Maintained by Adrian Dusa. Last updated 17 hours ago.
2 stars 6.74 score 110 scripts 4 dependents
shaunpwilkinson
aphid:Analysis with Profile Hidden Markov Models
Designed for the development and application of hidden Markov models and profile HMMs for biological sequence analysis. Contains functions for multiple and pairwise sequence alignment, model construction and parameter optimization, file import/export, implementation of the forward, backward and Viterbi algorithms for conditional sequence probabilities, tree-based sequence weighting, and sequence simulation. Features a wide variety of potential applications including database searching, gene-finding and annotation, phylogenetic analysis and sequence classification. Based on the models and algorithms described in Durbin et al (1998, ISBN: 9780521629713).
Maintained by Shaun Wilkinson. Last updated 9 months ago.
22 stars 6.58 score 38 scripts 3 dependents
jacekbialek
PriceIndices:Calculating Bilateral and Multilateral Price Indexes
Preparing a scanner data set for price dynamics calculations (data selecting, data classification, data matching, data filtering). Computing bilateral and multilateral indexes. For details on these methods see: Diewert and Fox (2020) <doi:10.1080/07350015.2020.1816176>, Białek (2019) <doi:10.2478/jos-2019-0014> or Białek (2020) <doi:10.2478/jos-2020-0037>.
Maintained by Jacek Białek. Last updated 2 months ago.
11 stars 6.02 score 16 scripts
openbiox
contribution:A Tiny Contribution Table Generator Based on 'ggplot2'
Contribution table for credit assignment based on 'ggplot2'. This can improve the author contribution information in academic journals and personal CV.
Maintained by Shixiang Wang. Last updated 2 years ago.
contributioncreditggplot2research
11 stars 5.20 score 29 scripts
mkorvink
archetyper:An Archetype for Data Mining and Data Science Projects
A project template to support the data science workflow.
Maintained by Michael Korvink. Last updated 4 years ago.
6 stars 4.78 score 7 scripts
bkeller2
mlmpower:Power Analysis and Data Simulation for Multilevel Models
A declarative language for specifying multilevel models, solving for population parameters based on specified variance-explained effect size measures, generating data, and conducting power analyses to determine sample size recommendations. The specification allows for any number of within-cluster effects, between-cluster effects, covariate effects at either level, and random coefficients. Moreover, the models do not assume orthogonal effects, and predictors can correlate at either level and accommodate models with multiple interaction effects.
Maintained by Brian T. Keller. Last updated 5 months ago.
3 stars 4.65 score 3 scripts
ecor
RGENERATE:Tools to Generate Vector Time Series
A method 'generate()' is implemented in this package for the random generation of vector time series according to models obtained by 'RMAWGEN', 'vars' or other packages. This package was created to generalize the algorithms of the 'RMAWGEN' package for the analysis and generation of any environmental vector time series.
Maintained by Emanuele Cordano. Last updated 8 months ago.
1 stars 4.38 score 16 scripts 1 dependents
aalfons
simFrame:Simulation Framework
A general framework for statistical simulation, which allows researchers to make use of a wide range of simulation designs with minimal programming effort. The package provides functionality for drawing samples from a distribution or a finite population, for adding outliers and missing values, as well as for visualization of the simulation results. It follows a clear object-oriented design and supports parallel computing to increase computational performance.
Maintained by Andreas Alfons. Last updated 3 years ago.
2 stars 3.90 score 80 scripts
plantbreedingbiometryaua2
rhoneycomb:Analysis of Honeycomb Selection Designs
A useful statistical tool for the construction and analysis of Honeycomb Selection Designs. More information about this type of designs: Fasoula V. (2013) <doi:10.1002/9781118497869.ch6> Fasoula V.A., and Tokatlidis I.S. (2012) <doi:10.1007/s13593-011-0034-0> Fasoulas A.C., and Fasoula V.A. (1995) <doi:10.1002/9780470650059.ch3> Tokatlidis I. (2016) <doi:10.1017/S0014479715000150> Tokatlidis I., and Vlachostergios D. (2016) <doi:10.3390/d8040029>.
Maintained by Nikos Antonetsis. Last updated 2 years ago.
3.70 score 2 scripts
tdjorgensen
simsem:SIMulated Structural Equation Modeling
Provides an easy framework for Monte Carlo simulation in structural equation modeling, which can be used for various purposes, such as such as model fit evaluation, power analysis, or missing data handling and planning.
Maintained by Terrence D. Jorgensen. Last updated 4 years ago.
3.40 score 276 scripts
bioc
Rtreemix:Rtreemix: Mutagenetic trees mixture models.
Rtreemix is a package that offers an environment for estimating the mutagenetic trees mixture models from cross-sectional data and using them for various predictions. It includes functions for fitting the trees mixture models, likelihood computations, model comparisons, waiting time estimations, stability analysis, etc.
Maintained by Jasmina Bogojeska. Last updated 1 months ago.
2.86 score 12 scripts
steppdev
stepp:Subpopulation Treatment Effect Pattern Plot (STEPP)
A method to explore the treatment-covariate interactions in survival or generalized linear model (GLM) for continuous, binomial and count data arising from two or more treatment arms of a clinical trial. A permutation distribution approach to inference is implemented, based on permuting the covariate values within each treatment group.
Maintained by Wai-ki Yip. Last updated 8 months ago.
2.75 score 28 scripts
matt-dray
emojiscape:Randomised Emoji Scenes
Print to the console a randomised scene composed of emoji.
Maintained by Matt Dray. Last updated 4 years ago.
2 stars 2.00 score 3 scripts
lafaye
ConvergenceConcepts:Seeing Convergence Concepts in Action
This is a pedagogical package, designed to help students understanding convergence of random variables. It provides a way to investigate interactively various modes of convergence (in probability, almost surely, in law and in mean) of a sequence of i.i.d. random variables. Visualisation of simulated sample paths is possible through interactive plots. The approach is illustrated by examples and exercises through the function 'investigate', as described in Lafaye de Micheaux and Liquet (2009) <doi:10.1198/tas.2009.0032>. The user can study his/her own sequences of random variables.
Maintained by Pierre Lafaye De Micheaux. Last updated 3 years ago.
1.00 score 10 scripts