Showing 111 of total 111 results (show query)
business-science
timetk:A Tool Kit for Working with Time Series
Easy visualization, wrangling, and feature engineering of time series data for forecasting and machine learning prediction. Consolidates and extends time series functionality from packages including 'dplyr', 'stats', 'xts', 'forecast', 'slider', 'padr', 'recipes', and 'rsample'.
Maintained by Matt Dancho. Last updated 1 years ago.
coercioncoercion-functionsdata-miningdplyrforecastforecastingforecasting-modelsmachine-learningseries-decompositionseries-signaturetibbletidytidyquanttidyversetimetime-seriestimeseries
26.8 match 625 stars 14.15 score 4.0k scripts 16 dependents
rebeccasalles
TSPred:Functions for Benchmarking Time Series Prediction
Functions for defining and conducting a time series prediction process including pre(post)processing, decomposition, modelling, prediction and accuracy assessment. The generated models and its yielded prediction errors can be used for benchmarking other time series prediction methods and for creating a demand for the refinement of such methods. For this purpose, benchmark data from prediction competitions may be used.
Maintained by Rebecca Pontes Salles. Last updated 4 years ago.
benchmarkinglinear-modelsmachine-learningnonstationaritytime-series-forecasttime-series-prediction
58.3 match 24 stars 5.53 score 94 scripts 1 dependents
kwstat
agridat:Agricultural Datasets
Datasets from books, papers, and websites related to agriculture. Example graphics and analyses are included. Data come from small-plot trials, multi-environment trials, uniformity trials, yield monitors, and more.
Maintained by Kevin Wright. Last updated 28 days ago.
18.6 match 125 stars 11.02 score 1.7k scripts 2 dependents
robjhyndman
Mcomp:Data from the M-Competitions
The 1001 time series from the M-competition (Makridakis et al. 1982) <DOI:10.1002/for.3980010202> and the 3003 time series from the IJF-M3 competition (Makridakis and Hibon, 2000) <DOI:10.1016/S0169-2070(00)00057-1>.
Maintained by Rob Hyndman. Last updated 9 months ago.
23.8 match 11 stars 7.13 score 288 scripts 2 dependents
echasnovski
comperes:Manage Competition Results
Tools for storing and managing competition results. Competition is understood as a set of games in which players gain some abstract scores. There are two ways for storing results: in long (one row per game-player) and wide (one row per game with fixed amount of players) formats. This package provides functions for creation and conversion between them. Also there are functions for computing their summary and Head-to-Head values for players. They leverage grammar of data manipulation from 'dplyr'.
Maintained by Evgeni Chasnovski. Last updated 2 years ago.
23.5 match 8 stars 6.28 score 40 scripts 1 dependents
eagerai
fastai:Interface to 'fastai'
The 'fastai' <https://docs.fast.ai/index.html> library simplifies training fast and accurate neural networks using modern best practices. It is based on research in to deep learning best practices undertaken at 'fast.ai', including 'out of the box' support for vision, text, tabular, audio, time series, and collaborative filtering models.
Maintained by Turgut Abdullayev. Last updated 11 months ago.
audiocollaborative-filteringdarknetdarknet-image-classificationfastaimedicalobject-detectiontabulartextvision
12.5 match 118 stars 9.40 score 76 scripts
ellisp
Tcomp:Data from the 2010 Tourism Forecasting Competition
The 1311 time series from the tourism forecasting competition conducted in 2010 and described in Athanasopoulos et al. (2011) <DOI:10.1016/j.ijforecast.2010.04.009>.
Maintained by Peter Ellis. Last updated 7 years ago.
19.0 match 5 stars 5.52 score 44 scripts 1 dependents
hankstevens
primer:Functions and Data for the Book, a Primer of Ecology with R
Functions are primarily functions for systems of ordinary differential equations, difference equations, and eigenanalysis and projection of demographic matrices; data are for examples.
Maintained by Hank Stevens. Last updated 4 years ago.
12.7 match 14 stars 5.92 score 118 scripts
famuvie
breedR:Statistical Methods for Forest Genetic Resources Analysts
Statistical tools to build predictive models for the breeders community. It aims to assess the genetic value of individuals under a number of situations, including spatial autocorrelation, genetic/environment interaction and competition. It is under active development as part of the Trees4Future project, particularly developed having forest genetic trials in mind. But can be used for animals or other situations as well.
Maintained by Facundo Muñoz. Last updated 8 months ago.
13.0 match 33 stars 5.44 score 24 scripts
krzjoa
m5:'M5 Forecasting' Challenges Data
Contains functions, which facilitate downloading, loading and preparing data from 'M5 Forecasting' challenges (by 'University of Nicosia', hosted on 'Kaggle'). The data itself is set of time series of different product sales in 'Walmart'. The package also includes a ready-to-use built-in M5 subset named 'tiny_m5'. For detailed information about the challenges, see: Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilis. (2020). The M5 Accuracy competition: Results, findings and conclusions. <doi:10.1016/j.ijforecast.2021.10.009>
Maintained by Krzysztof Joachimiak. Last updated 3 years ago.
data-sciencekaggle-competitionkaggle-datasetm5-competitionm5-forecastingtime-series-forecastingwalmartwalmart-sales-forecasting
15.5 match 2 stars 4.45 score 28 scripts
alarm-redist
redist:Simulation Methods for Legislative Redistricting
Enables researchers to sample redistricting plans from a pre-specified target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo algorithms. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements. Tools for analysis such as computation of various summary statistics and plotting functionality are also included. The package implements the SMC algorithm of McCartan and Imai (2023) <doi:10.1214/23-AOAS1763>, the enumeration algorithm of Fifield, Imai, Kawahara, and Kenny (2020) <doi:10.1080/2330443X.2020.1791773>, the Flip MCMC algorithm of Fifield, Higgins, Imai and Tarr (2020) <doi:10.1080/10618600.2020.1739532>, the Merge-split/Recombination algorithms of Carter et al. (2019) <arXiv:1911.01503> and DeFord et al. (2021) <doi:10.1162/99608f92.eb30390f>, and the Short-burst optimization algorithm of Cannon et al. (2020) <arXiv:2011.02288>.
Maintained by Christopher T. Kenny. Last updated 2 months ago.
geospatialgerrymanderingredistrictingsamplingopenblascppopenmp
7.5 match 68 stars 9.17 score 259 scripts
rstudio
gt:Easily Create Presentation-Ready Display Tables
Build display tables from tabular data with an easy-to-use set of functions. With its progressive approach, we can construct display tables with a cohesive set of table parts. Table values can be formatted using any of the included formatting functions. Footnotes and cell styles can be precisely added through a location targeting system. The way in which 'gt' handles things for you means that you don't often have to worry about the fine details.
Maintained by Richard Iannone. Last updated 11 days ago.
docxeasy-to-usehtmllatexrtfsummary-tables
3.5 match 2.1k stars 18.36 score 20k scripts 112 dependents
rudeboybert
forestecology:Fitting and Assessing Neighborhood Models of the Effect of Interspecific Competition on the Growth of Trees
Code for fitting and assessing models for the growth of trees. In particular for the Bayesian neighborhood competition linear regression model of Allen (2020): methods for model fitting and generating fitted/predicted values, evaluating the effect of competitor species identity using permutation tests, and evaluating model performance using spatial cross-validation.
Maintained by Albert Y. Kim. Last updated 3 years ago.
11.5 match 12 stars 5.12 score 11 scripts
ropensci
concstats:Market Structure, Concentration and Inequality Measures
Based on individual market shares of all participants in a market or space, the package offers a set of different structural and concentration measures frequently - and not so frequently - used in research and in practice. Measures can be calculated in groups or individually. The calculated measure or the resulting vector in table format should help practitioners make more informed decisions. Methods used in this package are from: 1. Chang, E. J., Guerra, S. M., de Souza Penaloza, R. A. & Tabak, B. M. (2005) "Banking concentration: the Brazilian case". 2. Cobham, A. and A. Summer (2013). "Is It All About the Tails? The Palma Measure of Income Inequality". 3. Garcia Alba Idunate, P. (1994). "Un Indice de dominancia para el analisis de la estructura de los mercados". 4. Ginevicius, R. and S. Cirba (2009). "Additive measurement of market concentration" <doi:10.3846/1611-1699.2009.10.191-198>. 5. Herfindahl, O. C. (1950), "Concentration in the steel industry" (PhD thesis). 6. Hirschmann, A. O. (1945), "National power and structure of foreign trade". 7. Melnik, A., O. Shy, and R. Stenbacka (2008), "Assessing market dominance" <doi:10.1016/j.jebo.2008.03.010>. 8. Palma, J. G. (2006). "Globalizing Inequality: 'Centrifugal' and 'Centripetal' Forces at Work". 9. Shannon, C. E. (1948). "A Mathematical Theory of Communication". 10. Simpson, E. H. (1949). "Measurement of Diversity" <doi:10.1038/163688a0>.
Maintained by Andreas Schneider. Last updated 1 years ago.
business-analyticscompetitionconcentrationdiversityinequalitypackage-development
10.0 match 7 stars 5.02 score 15 scripts
flavioleccese92
euroleaguer:Euroleague and Eurocup basketball API
Unofficial API wrapper for 'Euroleague' and 'Eurocup' basketball API (<https://www.euroleaguebasketball.net/en/euroleague/>), it allows to retrieve real-time and historical standard and advanced statistics about competitions, teams, players and games.
Maintained by Flavio Leccese. Last updated 2 months ago.
analyticsbasketballdatadata-sciencelibrary
12.1 match 7 stars 4.15 score 7 scripts
idsia
bayesRecon:Probabilistic Reconciliation via Conditioning
Provides methods for probabilistic reconciliation of hierarchical forecasts of time series. The available methods include analytical Gaussian reconciliation (Corani et al., 2021) <doi:10.1007/978-3-030-67664-3_13>, MCMC reconciliation of count time series (Corani et al., 2024) <doi:10.1016/j.ijforecast.2023.04.003>, Bottom-Up Importance Sampling (Zambon et al., 2024) <doi:10.1007/s11222-023-10343-y>, methods for the reconciliation of mixed hierarchies (Mix-Cond and TD-cond) (Zambon et al., 2024. The 40th Conference on Uncertainty in Artificial Intelligence, accepted).
Maintained by Dario Azzimonti. Last updated 2 months ago.
7.0 match 7 stars 7.13 score 40 scripts
mjg211
phaseR:Phase Plane Analysis of One- And Two-Dimensional Autonomous ODE Systems
Performs a qualitative analysis of one- and two-dimensional autonomous ordinary differential equation systems, using phase plane methods. Programs are available to identify and classify equilibrium points, plot the direction field, and plot trajectories for multiple initial conditions. In the one-dimensional case, a program is also available to plot the phase portrait. Whilst in the two-dimensional case, programs are additionally available to plot nullclines and stable/unstable manifolds of saddle points. Many example systems are provided for the user. For further details can be found in Grayling (2014) <doi:10.32614/RJ-2014-023>.
Maintained by Michael J Grayling. Last updated 3 years ago.
biological-modelingdifferential-equationsdynamical-systemsecological-modellinglotka-volterramanifoldsmodeling-dynamic-systemsmorris-lecarperturbation-analysisphase-planesir-modelspecies-interactionsvan-der-pol
7.0 match 15 stars 6.63 score 94 scripts 1 dependents
olafmersmann
emoa:Evolutionary Multiobjective Optimization Algorithms
Collection of building blocks for the design and analysis of evolutionary multiobjective optimization algorithms.
Maintained by Olaf Mersmann. Last updated 6 months ago.
7.1 match 8 stars 6.02 score 51 scripts 3 dependents
biometry
bipartite:Visualising Bipartite Networks and Calculating Some (Ecological) Indices
Functions to visualise webs and calculate a series of indices commonly used to describe pattern in (ecological) webs. It focuses on webs consisting of only two levels (bipartite), e.g. pollination webs or predator-prey-webs. Visualisation is important to get an idea of what we are actually looking at, while the indices summarise different aspects of the web's topology.
Maintained by Carsten F. Dormann. Last updated 7 days ago.
3.7 match 37 stars 10.93 score 592 scripts 15 dependents
lbbe-software
nlsMicrobio:Nonlinear Regression in Predictive Microbiology
Data sets and nonlinear regression models dedicated to predictive microbiology.
Maintained by Aurelie Siberchicot. Last updated 13 days ago.
7.0 match 1 stars 5.57 score 41 scripts 1 dependentsechasnovski
comperank:Ranking Methods for Competition Results
Compute ranking and rating based on competition results. Methods of different nature are implemented: with fixed Head-to-Head structure, with variable Head-to-Head structure and with iterative nature. All algorithms are taken from the book 'Who’s #1?: The science of rating and ranking' by Amy N. Langville and Carl D. Meyer (2012, ISBN:978-0-691-15422-0).
Maintained by Evgeni Chasnovski. Last updated 2 years ago.
6.7 match 24 stars 5.65 score 37 scripts
ogarciav
siplab:Spatial Individual-Plant Modelling
A platform for computing competition indices and experimenting with spatially explicit individual-based vegetation models.
Maintained by Oscar Garcia. Last updated 3 years ago.
plant-ecologyplant-growthsimulation
7.5 match 3 stars 4.97 score 31 scriptsbusiness-science
modeltime:The Tidymodels Extension for Time Series Modeling
The time series forecasting framework for use with the 'tidymodels' ecosystem. Models include ARIMA, Exponential Smoothing, and additional time series models from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" (<https://otexts.com/fpp2/>). Refer to "Prophet: forecasting at scale" (<https://research.facebook.com/blog/2017/02/prophet-forecasting-at-scale/>.).
Maintained by Matt Dancho. Last updated 5 months ago.
arimadata-sciencedeep-learningetsforecastingmachine-learningmachine-learning-algorithmsmodeltimeprophettbatstidymodelingtidymodelstimetime-seriestime-series-analysistimeseriestimeseries-forecasting
3.4 match 549 stars 10.57 score 1.1k scripts 7 dependents
wviechtb
metadat:Meta-Analysis Datasets
A collection of meta-analysis datasets for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.
Maintained by Wolfgang Viechtbauer. Last updated 2 days ago.
3.3 match 30 stars 10.54 score 65 scripts 93 dependentsrobjhyndman
tscompdata:Time series data from various forecasting competitions
Time series data from the following forecasting competitions are provided: M, M3, NN3, NN5, NNGC1, Tourism, and GEFCom2012.
Maintained by Rob Hyndman. Last updated 2 years ago.
7.2 match 18 stars 4.69 score 18 scripts
cran
drc:Analysis of Dose-Response Curves
Analysis of dose-response data is made available through a suite of flexible and versatile model fitting and after-fitting functions.
Maintained by Christian Ritz. Last updated 9 years ago.
4.0 match 8 stars 8.39 score 1.4k scripts 28 dependents
robjhyndman
cricketdata:International Cricket Data
Data on international and other major cricket matches from ESPNCricinfo <https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>. This package provides some functions to download the data into tibbles ready for analysis.
Maintained by Rob Hyndman. Last updated 1 years ago.
cricketcricket-dataozunconf17unconf
3.8 match 88 stars 7.84 score 87 scriptsalarm-redist
redistmetrics:Redistricting Metrics
Reliable and flexible tools for scoring redistricting plans using common measures and metrics. These functions provide key direct access to tools useful for non-simulation analyses of redistricting plans, such as for measuring compactness or partisan fairness. Tools are designed to work with the 'redist' package seamlessly.
Maintained by Christopher T. Kenny. Last updated 9 months ago.
3.8 match 10 stars 7.57 score 23 scripts 2 dependents
r-forge
Sleuth3:Data Sets from Ramsey and Schafer's "Statistical Sleuth (3rd Ed)"
Data sets from Ramsey, F.L. and Schafer, D.W. (2013), "The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed)", Cengage Learning.
Maintained by Berwin A Turlach. Last updated 1 years ago.
4.5 match 6.38 score 522 scripts
nixtla
nixtlar:A Software Development Kit for 'Nixtla''s 'TimeGPT'
A Software Development Kit for working with 'Nixtla''s 'TimeGPT', a foundation model for time series forecasting. 'API' is an acronym for 'application programming interface'; this package allows users to interact with 'TimeGPT' via the 'API'. You can set and validate 'API' keys and generate forecasts via 'API' calls. It is compatible with 'tsibble' and base R. For more details visit <https://docs.nixtla.io/>.
Maintained by Mariana Menchero. Last updated 28 days ago.
3.3 match 30 stars 8.16 score 38 scriptsr-forge
Sleuth2:Data Sets from Ramsey and Schafer's "Statistical Sleuth (2nd Ed)"
Data sets from Ramsey, F.L. and Schafer, D.W. (2002), "The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed)", Duxbury.
Maintained by Berwin A Turlach. Last updated 1 years ago.
4.5 match 5.70 score 191 scriptslbbe-software
nlstools:Tools for Nonlinear Regression Analysis
Several tools for assessing the quality of fit of a gaussian nonlinear model are provided.
Maintained by Aurelie Siberchicot. Last updated 13 days ago.
2.7 match 6 stars 9.42 score 528 scripts 7 dependentscran
comsimitv:Flexible Framework for Simulating Community Assembly
Flexible framework for trait-based simulation of community assembly, where components could be replaced by user-defined function and that allows variation of traits within species.
Maintained by Zoltan Botta-Dukat. Last updated 4 years ago.
12.0 match 2.00 score 3 scripts
aestears
plantTracker:Extract Demographic and Competition Data from Fine-Scale Maps
Extracts growth, survival, and local neighborhood density information from repeated, fine-scale maps of organism occurrence. Further information about this package can be found in our journal article, "plantTracker: An R package to translate maps of plant occurrence into demographic data" published in 2022 in Methods in Ecology and Evolution (Stears, et al., 2022) <doi:10.1111/2041-210X.13950>.
Maintained by Alice Stears. Last updated 2 years ago.
4.6 match 8 stars 5.18 score 19 scripts
bioc
limma:Linear Models for Microarray and Omics Data
Data analysis, linear models and differential expression for omics data.
Maintained by Gordon Smyth. Last updated 6 days ago.
exonarraygeneexpressiontranscriptionalternativesplicingdifferentialexpressiondifferentialsplicinggenesetenrichmentdataimportbayesianclusteringregressiontimecoursemicroarraymicrornaarraymrnamicroarrayonechannelproprietaryplatformstwochannelsequencingrnaseqbatcheffectmultiplecomparisonnormalizationpreprocessingqualitycontrolbiomedicalinformaticscellbiologycheminformaticsepigeneticsfunctionalgenomicsgeneticsimmunooncologymetabolomicsproteomicssystemsbiologytranscriptomics
1.7 match 13.81 score 16k scripts 585 dependentsbioc
edgeR:Empirical Analysis of Digital Gene Expression Data in R
Differential expression analysis of sequence count data. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models, quasi-likelihood, and gene set enrichment. Can perform differential analyses of any type of omics data that produces read counts, including RNA-seq, ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE, CAGE, metabolomics, or proteomics spectral counts. RNA-seq analyses can be conducted at the gene or isoform level, and tests can be conducted for differential exon or transcript usage.
Maintained by Yunshun Chen. Last updated 6 days ago.
alternativesplicingbatcheffectbayesianbiomedicalinformaticscellbiologychipseqclusteringcoveragedifferentialexpressiondifferentialmethylationdifferentialsplicingdnamethylationepigeneticsfunctionalgenomicsgeneexpressiongenesetenrichmentgeneticsimmunooncologymultiplecomparisonnormalizationpathwaysproteomicsqualitycontrolregressionrnaseqsagesequencingsinglecellsystemsbiologytimecoursetranscriptiontranscriptomicsopenblas
1.7 match 13.40 score 17k scripts 255 dependents
rekyt
fdcoexist:Multi-Species Trait-Based Coexistence Model in Discrete time
A modified Beverton-Holt model used in the Denelle, Grenié et al. manuscript that expresses environmental filtering, limiting similarity and hierarchical competition explicitely in function of species traits. This package provides all the code necessary to rerun the analyses of the manuscript.
Maintained by Matthias Grenié. Last updated 2 years ago.
7.4 match 2.70 score 1 scriptscran
gamair:Data for 'GAMs: An Introduction with R'
Data sets and scripts used in the book 'Generalized Additive Models: An Introduction with R', Wood (2006,2017) CRC.
Maintained by Simon Wood. Last updated 6 years ago.
7.8 match 2.43 score 162 scripts
jaseziv
worldfootballR:Extract and Clean World Football (Soccer) Data
Allow users to obtain clean and tidy football (soccer) game, team and player data. Data is collected from a number of popular sites, including 'FBref', transfer and valuations data from 'Transfermarkt'<https://www.transfermarkt.com/> and shooting location and other match stats data from 'Understat'<https://understat.com/>. It gives users the ability to access data more efficiently, rather than having to export data tables to files before being able to complete their analysis.
Maintained by Jason Zivkovic. Last updated 1 months ago.
fbreffootballfootball-datasoccer-datasports-datatransfermarktunderstat
1.9 match 506 stars 9.89 score 516 scripts 2 dependentsbioc
PepSetTest:Peptide Set Test
Peptide Set Test (PepSetTest) is a peptide-centric strategy to infer differentially expressed proteins in LC-MS/MS proteomics data. This test detects coordinated changes in the expression of peptides originating from the same protein and compares these changes against the rest of the peptidome. Compared to traditional aggregation-based approaches, the peptide set test demonstrates improved statistical power, yet controlling the Type I error rate correctly in most cases. This test can be valuable for discovering novel biomarkers and prioritizing drug targets, especially when the direct application of statistical analysis to protein data fails to provide substantial insights.
Maintained by Junmin Wang. Last updated 5 months ago.
differentialexpressionregressionproteomicsmassspectrometry
3.7 match 2 stars 5.00 score 9 scripts
laresbernardo
lares:Analytics & Machine Learning Sidekick
Auxiliary package for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, Marketing Mix Modeling (Robyn), Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or advanced R programming skills.
Maintained by Bernardo Lares. Last updated 24 days ago.
analyticsapiautomationautomldata-sciencedescriptive-statisticsh2omachine-learningmarketingmmmpredictive-modelingpuzzlerlanguagerobynvisualization
1.8 match 233 stars 9.84 score 185 scripts 1 dependents
jverzani
UsingR:Data Sets, Etc. for the Text "Using R for Introductory Statistics", Second Edition
A collection of data sets to accompany the textbook "Using R for Introductory Statistics," second edition.
Maintained by John Verzani. Last updated 3 years ago.
3.5 match 1 stars 4.97 score 1.4k scripts
statmanrobin
Stat2Data:Datasets for Stat2
Datasets for the textbook Stat2: Modeling with Regression and ANOVA (second edition). The package also includes data for the first edition, Stat2: Building Models for a World of Data and a few functions for plotting diagnostics.
Maintained by Robin Lock. Last updated 6 years ago.
3.5 match 5 stars 4.94 score 544 scripts
thiyangt
tsdataleaks:Exploit Data Leakages in Time Series Forecasting Competitions
Forecasting competitions are of increasing importance as a mean to learn best practices and gain knowledge. Data leakage is one of the most common issues that can often be found in competitions. Data leaks can happen when the training data contains information about the test data. For example: randomly chosen blocks of time series are concatenated to form a new time series, scale-shifts, repeating patterns in time series, white noise is added in the original time series to form a new time series, etc. 'tsdataleaks' package can be used to detect data leakages in a collection of time series.
Maintained by Thiyanga S. Talagala. Last updated 1 years ago.
3.6 match 3 stars 4.18 score 8 scriptscran
MCI:Multiplicative Competitive Interaction (MCI) Model
Market area models are used to analyze and predict store choices and market areas concerning retail and service locations. This package implements two market area models (Huff Model, Multiplicative Competitive Interaction Model) into R, while the emphases lie on 1.) fitting these models based on empirical data via OLS regression and nonlinear techniques and 2.) data preparation and processing (esp. interaction matrices and data preparation for the MCI Model).
Maintained by Thomas Wieland. Last updated 7 years ago.
5.3 match 2.53 score 42 scripts
steps-dev
steps:Spatially- and Temporally-Explicit Population Simulator
Software to simulate population change across space and time. Visintin et al. (2020) <doi:10.1111/2041-210X.13354>.
Maintained by Casey Visintin. Last updated 1 years ago.
2.0 match 18 stars 6.66 score 84 scripts
egenn
rtemis:Machine Learning and Visualization
Advanced Machine Learning and Visualization. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and interactive graphics.
Maintained by E.D. Gennatas. Last updated 1 months ago.
data-sciencedata-visualizationmachine-learningmachine-learning-libraryvisualization
1.9 match 145 stars 7.09 score 50 scripts 2 dependents
moderndive
moderndive:Tidyverse-Friendly Introductory Linear Regression
Datasets and wrapper functions for tidyverse-friendly introductory linear regression, used in "Statistical Inference via Data Science: A ModernDive into R and the Tidyverse" available at <https://moderndive.com/>.
Maintained by Albert Y. Kim. Last updated 3 months ago.
1.1 match 88 stars 11.35 score 1.8k scripts
kenaho1
asbio:A Collection of Statistical Tools for Biologists
Contains functions from: Aho, K. (2014) Foundational and Applied Statistics for Biologists using R. CRC/Taylor and Francis, Boca Raton, FL, ISBN: 978-1-4398-7338-0.
Maintained by Ken Aho. Last updated 2 months ago.
1.7 match 5 stars 7.32 score 310 scripts 3 dependents
ehsan66
ICAOD:Optimal Designs for Nonlinear Statistical Models by Imperialist Competitive Algorithm (ICA)
Finds optimal designs for nonlinear models using a metaheuristic algorithm called Imperialist Competitive Algorithm (ICA). See, for details, Masoudi et al. (2017) <doi:10.1016/j.csda.2016.06.014> and Masoudi et al. (2019) <doi:10.1080/10618600.2019.1601097>.
Maintained by Ehsan Masoudi. Last updated 4 years ago.
4.9 match 2.49 score 31 scripts
stefanomp
massiveGST:Competitive Gene Sets Test with the Mann-Whitney-Wilcoxon Test
Friendly implementation of the Mann-Whitney-Wilcoxon test for competitive gene set enrichment analysis.
Maintained by Stefano Maria Pagnotta. Last updated 2 years ago.
3.4 match 2 stars 3.60 score 20 scripts
radicalcommecol
cxr:A Toolbox for Modelling Species Coexistence in R
Recent developments in modern coexistence theory have advanced our understanding on how species are able to persist and co-occur with other species at varying abundances. However, applying this mathematical framework to empirical data is still challenging, precluding a larger adoption of the theoretical tools developed by empiricists. This package provides a complete toolbox for modelling interaction effects between species, and calculate fitness and niche differences. The functions are flexible, may accept covariates, and different fitting algorithms can be used. A full description of the underlying methods is available in García-Callejas, D., Godoy, O., and Bartomeus, I. (2020) <doi:10.1111/2041-210X.13443>. Furthermore, the package provides a series of functions to calculate dynamics for stage-structured populations across sites.
Maintained by David Garcia-Callejas. Last updated 1 months ago.
1.8 match 10 stars 6.51 score 27 scripts
thijsjanzen
STEPCAM:ABC-SMC Inference of STEPCAM
Collection of model estimation, and model plotting functions related to the STEPCAM family of community assembly models. STEPCAM is a STEPwise Community Assembly Model that infers the relative contribution of Dispersal Assembly, Habitat Filtering and Limiting Similarity from a dataset consisting of the combination of trait and abundance data. See also <http://onlinelibrary.wiley.com/wol1/doi/10.1890/14-0454.1/abstract> for more information.
Maintained by Thijs Janzen. Last updated 4 years ago.
2.3 match 6 stars 4.89 score 13 scriptsbioc
EnrichmentBrowser:Seamless navigation through combined results of set-based and network-based enrichment analysis
The EnrichmentBrowser package implements essential functionality for the enrichment analysis of gene expression data. The analysis combines the advantages of set-based and network-based enrichment analysis in order to derive high-confidence gene sets and biological pathways that are differentially regulated in the expression data under investigation. Besides, the package facilitates the visualization and exploration of such sets and pathways.
Maintained by Ludwig Geistlinger. Last updated 5 months ago.
immunooncologymicroarrayrnaseqgeneexpressiondifferentialexpressionpathwaysgraphandnetworknetworkgenesetenrichmentnetworkenrichmentvisualizationreportwriting
1.2 match 20 stars 9.37 score 164 scripts 3 dependents
yiluheihei
RevEcoR:Reverse Ecology Analysis on Microbiome
An implementation of the reverse ecology framework. Reverse ecology refers to the use of genomics to study ecology with no a priori assumptions about the organism(s) under consideration, linking organisms to their environment. It allows researchers to reconstruct the metabolic networks and study the ecology of poorly characterized microbial species from their genomic information, and has substantial potentials for microbial community ecological analysis.
Maintained by Yang Cao. Last updated 6 years ago.
1.8 match 6 stars 5.77 score 22 scripts 1 dependentsbioc
target:Predict Combined Function of Transcription Factors
Implement the BETA algorithm for infering direct target genes from DNA-binding and perturbation expression data Wang et al. (2013) <doi: 10.1038/nprot.2013.150>. Extend the algorithm to predict the combined function of two DNA-binding elements from comprable binding and expression data.
Maintained by Mahmoud Ahmed. Last updated 5 months ago.
softwarestatisticalmethodtranscriptionalgorithmchip-seqdna-bindinggene-regulationtranscription-factors
1.3 match 4 stars 7.79 score 1.3k scripts
jimmyday12
monashtipr:An R API Wrapper for the Monash University Probabilistic Footy Tipping Competition
An API wrapper for the 'Monash University Probabilistic Footy Tipping Competition' <https://probabilistic-footy.monash.edu/~footy/index.shtml>. Allows users to submit tips directly to the competition from R.
Maintained by James Day. Last updated 1 years ago.
3.6 match 1 stars 2.74 score 11 scripts
mchlbckr
MSBStatsData:Package Containing Data for My Statistics Courses at the Münster School of Business
Package containing data for my statistics courses at the Münster School of Business.
Maintained by Michael Bücker. Last updated 1 years ago.
3.6 match 2.70 scorebioc
TMSig:Tools for Molecular Signatures
The TMSig package contains tools to prepare, analyze, and visualize named lists of sets, with an emphasis on molecular signatures (such as gene or kinase sets). It includes fast, memory efficient functions to construct sparse incidence and similarity matrices and filter, cluster, invert, and decompose sets. Additionally, bubble heatmaps can be created to visualize the results of any differential or molecular signatures analysis.
Maintained by Tyler Sagendorf. Last updated 5 months ago.
clusteringgenesetenrichmentgraphandnetworkpathwaysvisualizationgene-setsmolecular-signatures
1.7 match 4 stars 5.60 score 4 scripts
ajwills72
catlearn:Formal Psychological Models of Categorization and Learning
Formal psychological models of categorization and learning, independently-replicated data sets against which to test them, and simulation archives.
Maintained by Andy Wills. Last updated 3 months ago.
categorizationcognitive-scienceformal-modelslearninglearning-theoryopen-modelsopen-sciencepsychologycpp
1.8 match 26 stars 5.25 score 46 scripts
jeroenpullens
NUCOMBog:NUtrient Cycling and COMpetition Model Undisturbed Open Bog Ecosystems in a Temperate to Sub-Boreal Climate
Modelling the vegetation, carbon, nitrogen and water dynamics of undisturbed open bog ecosystems in a temperate to sub-boreal climate. The executable of the model can downloaded from <https://github.com/jeroenpullens/NUCOMBog>.
Maintained by J.W.M. Pullens. Last updated 7 years ago.
2.7 match 1 stars 3.36 score 46 scriptscran
EcoVirtual:Simulation of Ecological Models
Computer simulations of classical ecological models as a learning resource.
Maintained by Alexandre Adalardo de Oliveira. Last updated 6 years ago.
5.8 match 1.48 score 1 dependents
victor-navarro
calmr:Canonical Associative Learning Models and their Representations
Implementations of canonical associative learning models, with tools to run experiment simulations, estimate model parameters, and compare model representations. Experiments and results are represented using S4 classes and methods.
Maintained by Victor Navarro. Last updated 9 months ago.
1.3 match 3 stars 6.40 score 17 scripts
luciu5
trade:Tools for Trade Practitioners
A collection of tools for trade practitioners, including the ability to calibrate different consumer demand systems and simulate the effects of tariffs and quotas under different competitive regimes. These tools are derived from Anderson et al. (2001) <doi:10.1016/S0047-2727(00)00085-2> and Froeb et al. (2003) <doi:10.1016/S0304-4076(02)00166-5>.
Maintained by Charles Taragin. Last updated 3 years ago.
2.3 match 1 stars 3.48 score 6 scripts 1 dependents
kisungyou
Riemann:Learning with Data on Riemannian Manifolds
We provide a variety of algorithms for manifold-valued data, including Fréchet summaries, hypothesis testing, clustering, visualization, and other learning tasks. See Bhattacharya and Bhattacharya (2012) <doi:10.1017/CBO9781139094764> for general exposition to statistics on manifolds.
Maintained by Kisung You. Last updated 2 years ago.
1.9 match 10 stars 3.70 score 8 scripts
temp20250212
MultiTraits:Analyzing and Visualizing Multidimensional Plant Traits
Implements analytical methods for multidimensional plant traits, including Competitors-Stress tolerators-Ruderals strategy analysis using leaf traits, Leaf-Height-Seed strategy analysis, Niche Periodicity Table analysis, and Trait Network analysis. Provides functions for data analysis, visualization, and network metrics calculation. Methods are based on Grime (1974) <doi:10.1038/250026a0>, Pierce et al. (2017) <doi:10.1111/1365-2435.12882>, Westoby (1998) <doi:10.1023/A:1004327224729>, Yang et al. (2022) <doi:10.1016/j.foreco.2022.120540>, Winemiller et al. (2015) <doi:10.1111/ele.12462>, He et al. (2020) <doi:10.1016/j.tree.2020.06.003>.
Maintained by Anonymous Author. Last updated 23 days ago.
1.8 match 3.90 score 16 scripts
shixinrui
SubpathwayLNCE:Identify Signal Subpathways Competitively Regulated by LncRNAs Based on ceRNA Theory
Identify dysfunctional subpathways competitively regulated by lncRNAs through integrating lncRNA-mRNA expression profile and pathway topologies.
Maintained by Xinrui Shi. Last updated 9 years ago.
statisticssupathwayslncrnasenrichment analysiscerna
3.3 match 2.00 score 2 scriptscran
ggscidca:Plotting Decision Curve Analysis with Coloured Bars
Decision curve analysis is a method for evaluating and comparing prediction models that incorporates clinical consequences, requires only the data set on which the models are tested, and can be applied to models that have either continuous or dichotomous results. The 'ggscidca' package adds coloured bars of discriminant relevance to the traditional decision curve. Improved practicality and aesthetics. This method was described by Balachandran VP (2015) <doi:10.1016/S1470-2045(14)71116-7>.
Maintained by Qiang Liu. Last updated 10 months ago.
3.8 match 1.70 score
eric-lamb
sesem:Spatially Explicit Structural Equation Modeling
Structural equation modeling is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with inter-correlated dependent and independent variables. Here we implement a simple method for spatially explicit structural equation modeling based on the analysis of variance co-variance matrices calculated across a range of lag distances. This method provides readily interpreted plots of the change in path coefficients across scale.
Maintained by Eric Lamb. Last updated 9 years ago.
4.0 match 2 stars 1.58 score 19 scripts
impaug
GDAdata:Datasets for the Book Graphical Data Analysis with R
Datasets used in the book 'Graphical Data Analysis with R' (Antony Unwin, CRC Press 2015).
Maintained by Antony Unwin. Last updated 10 years ago.
3.4 match 1.56 score 36 scripts
paulhendricks
titanic:Titanic Passenger Survival Data Set
This data set provides information on the fate of passengers on the fatal maiden voyage of the ocean liner "Titanic", with variables such as economic status (class), sex, age, and survival. Whereas the base R Titanic data found by calling data("Titanic") is an array resulting from cross-tabulating 2201 observations, these data sets are individual non-aggregated observations and formatted in a machine learning context with a training sample, a testing sample, and two additional data sets that can be used for deeper machine learning analysis. These data sets are used in a very well known Kaggle competition; formatting the raw data sets in a package hopefully lowers the barrier to entry for users new to R and machine learning.
Maintained by Paul Hendricks. Last updated 8 years ago.
0.5 match 10 stars 8.95 score 804 scripts 2 dependents
jameslamb
lightgbm:Light Gradient Boosting Machine
Tree based algorithms can be improved by introducing boosting frameworks. 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>. This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple machines.
Maintained by James Lamb. Last updated 1 months ago.
0.5 match 1 stars 8.47 score 1.6k scripts 6 dependents
vmielecnrs
econetwork:Analyzing Ecological Networks
A collection of advanced tools, methods and models specifically designed for analyzing different types of ecological networks - especially antagonistic (food webs, host-parasite), mutualistic (plant-pollinator, plant-fungus, etc) and competitive networks, as well as their variability in time and space. Statistical models are developed to describe and understand the mechanisms that determine species interactions, and to decipher the organization of these ecological networks (Ohlmann et al. (2019) <doi:10.1111/ele.13221>, Gonzalez et al. (2020) <doi:10.1101/2020.04.02.021691>, Miele et al. (2021) <doi:10.48550/arXiv.2103.10433>, Botella et al (2021) <doi:10.1111/2041-210X.13738>).
Maintained by Vincent Miele. Last updated 2 years ago.
3.8 match 1.04 score 11 scripts
skranz
repgame:Solve discounted repeated games with monetary transfers
Solve discounted repeated games with monetary transfers using the fast Algorithms develeoped by Goldluecke and Kranz (JET, 2013)
Maintained by Sebastian Kranz. Last updated 7 years ago.
1.9 match 2 stars 2.00 score 3 scripts
agvico
SDEFSR:Subgroup Discovery with Evolutionary Fuzzy Systems
Implementation of evolutionary fuzzy systems for the data mining task called "subgroup discovery". In particular, the algorithms presented in this package are: M. J. del Jesus, P. Gonzalez, F. Herrera, M. Mesonero (2007) <doi:10.1109/TFUZZ.2006.890662> M. J. del Jesus, P. Gonzalez, F. Herrera (2007) <doi:10.1109/MCDM.2007.369416> C. J. Carmona, P. Gonzalez, M. J. del Jesus, F. Herrera (2010) <doi:10.1109/TFUZZ.2010.2060200> C. J. Carmona, V. Ruiz-Rodado, M. J. del Jesus, A. Weber, M. Grootveld, P. González, D. Elizondo (2015) <doi:10.1016/j.ins.2014.11.030> It also provide a Shiny App to ease the analysis. The algorithms work with data sets provided in KEEL, ARFF and CSV format and also with data.frame objects.
Maintained by Angel M. Garcia. Last updated 4 years ago.
1.3 match 2.53 score 34 scripts
trackerproject
trackeR:Infrastructure for Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices
Provides infrastructure for handling running, cycling and swimming data from GPS-enabled tracking devices within R. The package provides methods to extract, clean and organise workout and competition data into session-based and unit-aware data objects of class 'trackeRdata' (S3 class). The information can then be visualised, summarised, and analysed through flexible and extensible methods. Frick and Kosmidis (2017) <doi: 10.18637/jss.v082.i07>, which is updated and maintained as one of the vignettes, provides detailed descriptions of the package and its methods, and real-data demonstrations of the package functionality.
Maintained by Ioannis Kosmidis. Last updated 1 years ago.
0.5 match 90 stars 6.37 score 58 scripts 1 dependentscran
adwordsR:Access the 'Google Adwords' API
Allows access to selected services that are part of the 'Google Adwords' API <https://developers.google.com/adwords/api/docs/guides/start>. 'Google Adwords' is an online advertising service by 'Google', that delivers Ads to users. This package offers a authentication process using 'OAUTH2'. Currently, there are two methods of data of accessing the API, depending on the type of request. One method uses 'SOAP' requests which require building an 'XML' structure and then sent to the API. These are used for the 'ManagedCustomerService' and the 'TargetingIdeaService'. The second method is by building 'AWQL' queries for the reporting side of the 'Google Adwords' API.
Maintained by Sean Longthorpe. Last updated 7 years ago.
1.9 match 1.70 scoreluciu5
antitrust:Tools for Antitrust Practitioners
A collection of tools for antitrust practitioners, including the ability to calibrate different consumer demand systems and simulate the effects of mergers under different competitive regimes.
Maintained by Charles Taragin. Last updated 6 months ago.
0.5 match 5 stars 5.64 score 36 scripts 2 dependentscran
flexclust:Flexible Cluster Algorithms
The main function kcca implements a general framework for k-centroids cluster analysis supporting arbitrary distance measures and centroid computation. Further cluster methods include hard competitive learning, neural gas, and QT clustering. There are numerous visualization methods for cluster results (neighborhood graphs, convex cluster hulls, barcharts of centroids, ...), and bootstrap methods for the analysis of cluster stability.
Maintained by Bettina Grün. Last updated 17 days ago.
0.5 match 3 stars 5.81 score 52 dependentsbioc
SPONGE:Sparse Partial Correlations On Gene Expression
This package provides methods to efficiently detect competitive endogeneous RNA interactions between two genes. Such interactions are mediated by one or several miRNAs such that both gene and miRNA expression data for a larger number of samples is needed as input. The SPONGE package now also includes spongEffects: ceRNA modules offer patient-specific insights into the miRNA regulatory landscape.
Maintained by Markus List. Last updated 5 months ago.
geneexpressiontranscriptiongeneregulationnetworkinferencetranscriptomicssystemsbiologyregressionrandomforestmachinelearning
0.5 match 5.36 score 38 scripts 1 dependents
span-18
spStack:Bayesian Geostatistics Using Predictive Stacking
Fits Bayesian hierarchical spatial process models for point-referenced Gaussian, Poisson, binomial, and binary data using stacking of predictive densities. It involves sampling from analytically available posterior distributions conditional upon some candidate values of the spatial process parameters and, subsequently assimilate inference from these individual posterior distributions using Bayesian predictive stacking. Our algorithm is highly parallelizable and hence, much faster than traditional Markov chain Monte Carlo algorithms while delivering competitive predictive performance. See Zhang, Tang, and Banerjee (2024) <doi:10.48550/arXiv.2304.12414>, and, Pan, Zhang, Bradley, and Banerjee (2024) <doi:10.48550/arXiv.2406.04655> for details.
Maintained by Soumyakanti Pan. Last updated 11 days ago.
0.5 match 4.95 score 6 scripts
kurthornik
cclust:Convex Clustering Methods and Clustering Indexes
Convex Clustering methods, including K-means algorithm, On-line Update algorithm (Hard Competitive Learning) and Neural Gas algorithm (Soft Competitive Learning), and calculation of several indexes for finding the number of clusters in a data set.
Maintained by Kurt Hornik. Last updated 2 years ago.
0.8 match 2.95 score 47 scripts 1 dependents
gpilgrim2670
SwimmeR:Data Import, Cleaning, and Conversions for Swimming Results
The goal of the 'SwimmeR' package is to provide means of acquiring, and then analyzing, data from swimming (and diving) competitions. To that end 'SwimmeR' allows results to be read in from .html sources, like 'Hy-Tek' real time results pages, '.pdf' files, 'ISL' results, 'Omega' results, and (on a development basis) '.hy3' files. Once read in, 'SwimmeR' can convert swimming times (performances) between the computationally useful format of seconds reported to the '100ths' place (e.g. 95.37), and the conventional reporting format (1:35.37) used in the swimming community. 'SwimmeR' can also score meets in a variety of formats with user defined point values, convert times between courses ('LCM', 'SCM', 'SCY') and draw single elimination brackets, as well as providing a suite of tools for working cleaning swimming data. This is a developmental package, not yet mature.
Maintained by Greg Pilgrim. Last updated 2 years ago.
0.5 match 4 stars 4.53 score 17 scripts
uni-arya
stepdownfdp:A Step-Down Procedure to Control the False Discovery Proportion
Provides a step-down procedure for controlling the False Discovery Proportion (FDP) in a competition-based setup, implementing Dong et al. (2020) <arXiv:2011.11939>. Such setups include target-decoy competition (TDC) in computational mass spectrometry and the knockoff construction in linear regression.
Maintained by Arya Ebadi. Last updated 3 years ago.
0.8 match 2.70 score 1 scripts
pechiyappan
data360r:Wrapper for 'TCdata360' and 'Govdata360' API
Makes it easy to engage with the Application Program Interface (API) of the 'TCdata360' and 'Govdata360' platforms at <https://tcdata360.worldbank.org/> and <https://govdata360.worldbank.org/>, respectively. These application program interfaces provide access to over 5000 trade, competitiveness, and governance indicator data, metadata, and related information from sources both inside and outside the World Bank Group. Package functions include easier download of data sets, metadata, and related information, as well as searching based on user-inputted query.
Maintained by Ramin Aliyev. Last updated 3 years ago.
0.5 match 24 stars 4.08 score 9 scripts
alsabtay
ATAforecasting:Automatic Time Series Analysis and Forecasting using the Ata Method
The Ata method (Yapar et al. (2019) <doi:10.15672/hujms.461032>), an alternative to exponential smoothing (described in Yapar (2016) <doi:10.15672/HJMS.201614320580>, Yapar et al. (2017) <doi:10.15672/HJMS.2017.493>), is a new univariate time series forecasting method which provides innovative solutions to issues faced during the initialization and optimization stages of existing forecasting methods. Forecasting performance of the Ata method is superior to existing methods both in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or seasonal time series which can be decomposed into four components (remainder, level, trend and seasonal). This methodology performed well on the M3 and M4-competition data. This package was written based on Ali Sabri Taylan’s PhD dissertation.
Maintained by Ali Sabri Taylan. Last updated 2 years ago.
ataataforecastingfableforecastforecastingtime-seriescpp
0.5 match 5 stars 3.88 score 4 scripts 1 dependents
celevitz
touRnamentofchampions:Tournament of Champions Data
Several datasets which describe the challenges and results of competitions in Tournament of Champions. This data is useful for practicing data wrangling, graphing, and analyzing how each season of Tournament of Champions played out.
Maintained by Levitz Carly. Last updated 7 days ago.
0.5 match 3.70 score
rosdyana
ROpenDota:Access OpenDota Services in R
Provides a client for the API of OpenDota. OpenDota is a web service which is provide DOTA2 real time data. Data is collected through the Steam WebAPI. With ROpenDota you can easily grab the latest DOTA2 statistics in R programming such as latest match on official international competition, analyzing your or enemy performance to learn their strategies,etc. Please see <https://github.com/rosdyana/ROpenDota> for more information.
Maintained by Rosdyana Kusuma. Last updated 6 years ago.
0.5 match 6 stars 3.76 score 19 scripts
johannes-titz
passt:Probability Associator Time (PASS-T)
Simulates judgments of frequency and duration based on the Probability Associator Time (PASS-T) model. PASS-T is a memory model based on a simple competitive artificial neural network. It can imitate human judgments of frequency and duration, which have been extensively studied in cognitive psychology (e.g. Hintzman (1970) <doi:10.1037/h0028865>, Betsch et al. (2010) <https://psycnet.apa.org/record/2010-18204-003>). The PASS-T model is an extension of the PASS model (Sedlmeier, 2002, ISBN:0198508638). The package provides an easy way to run simulations, which can then be compared with empirical data in human judgments of frequency and duration.
Maintained by Johannes Titz. Last updated 4 years ago.
0.5 match 3.70 score 3 scripts
freejstone
groupwalk:Implement the Group Walk Algorithm
A procedure that uses target-decoy competition (or knockoffs) to reject multiple hypotheses in the presence of group structure. The procedure controls the false discovery rate (FDR) at a user-specified threshold.
Maintained by Jack Freestone. Last updated 3 years ago.
0.5 match 2.70 score 1 scripts
katie-frank
combinedevents:Calculate Scores and Marks for Track and Field Combined Events
Includes functions to calculate scores and marks for track and field combined events competitions. The functions are based on the scoring tables for combined events set forth by the International Association of Athletics Federation (2001).
Maintained by Katie Frank. Last updated 4 years ago.
0.5 match 1 stars 2.70 score 2 scripts
gdurif
funStatTest:Statistical Testing for Functional Data
Implementation of two sample comparison procedures based on median-based statistical tests for functional data, introduced in Smida et al (2022) <doi:10.1080/10485252.2022.2064997>. Other competitive state-of-the-art approaches proposed by Chakraborty and Chaudhuri (2015) <doi:10.1093/biomet/asu072>, Horvath et al (2013) <doi:10.1111/j.1467-9868.2012.01032.x> or Cuevas et al (2004) <doi:10.1016/j.csda.2003.10.021> are also included in the package, as well as procedures to run test result comparisons and power analysis using simulations.
Maintained by Ghislain Durif. Last updated 10 months ago.
0.5 match 2.70 score 4 scripts
cran
SeqDetect:Sequence and Latent Process Detector
Sequence detector in this package contains a specific automaton model that can be used to learn and detect data and process sequences. Automaton model in this package is capable of learning and tracing sequences. Automaton model can be found in Krleža, Vrdoljak, Brčić (2019) <doi:10.1109/ACCESS.2019.2955245>. This research has been partly supported under Competitiveness and Cohesion Operational Programme from the European Regional and Development Fund, as part of the Integrated Anti-Fraud System project no. KK.01.2.1.01.0041. This research has also been partly supported by the European Regional Development Fund under the grant KK.01.1.1.01.0009.
Maintained by Dalibor Krleža. Last updated 5 years ago.
0.5 match 2.00 score 2 scripts
dvrbts
coenoflex:Gradient-Based Coenospace Vegetation Simulator
Simulates the composition of samples of vegetation according to gradient-based vegetation theory. Features a flexible algorithm incorporating competition and complex multi-gradient interaction.
Maintained by David W. Roberts. Last updated 8 years ago.
0.5 match 1.00 score 2 scriptscran
crsnls:Nonlinear Regression Parameters Estimation by 'CRS4HC' and 'CRS4HCe'
Functions for nonlinear regression parameters estimation by algorithms based on Controlled Random Search algorithm. Both functions (crs4hc(), crs4hce()) adapt current search strategy by four heuristics competition. In addition, crs4hce() improves adaptability by adaptive stopping condition.
Maintained by Tomáš Goryl. Last updated 9 years ago.
0.5 match 1.00 scorecran
swa:Subsampling Winner Algorithm for Classification
This algorithm conducts variable selection in the classification setting. It repeatedly subsamples variables and runs linear discriminant analysis (LDA) on the subsampled variables. Variables are scored based on the AUC and the t-statistics. Variables then enter a competition and the semi-finalist variables will be evaluated in a final round of LDA classification. The algorithm then outputs a list of variable selected. Qiao, Sun and Fan (2017) <http://people.math.binghamton.edu/qiao/swa.html>.
Maintained by Xingye Qiao. Last updated 7 years ago.
0.5 match 1.00 score 1 scripts
