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rinterface

argonR:R Interface to Argon HTML Design

R wrapper around the argon HTML library. More at <https://demos.creative-tim.com/argon-design-system/>.

Maintained by David Granjon. Last updated 1 years ago.

7.1 match 53 stars 7.80 score 131 scripts 3 dependents

r-spatial

spdep:Spatial Dependence: Weighting Schemes, Statistics

A collection of functions to create spatial weights matrix objects from polygon 'contiguities', from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree; a collection of tests for spatial 'autocorrelation', including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord' (1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel' general cross product statistic, Empirical Bayes estimates and 'Assunรงรฃo/Reis' (1999) <doi:10.1002/(SICI)1097-0258(19990830)18:16%3C2147::AID-SIM179%3E3.0.CO;2-I> Index, 'Getis/Ord' G ('Getis' and 'Ord' 1992) <doi:10.1111/j.1538-4632.1992.tb00261.x> and multicoloured join count statistics, 'APLE' ('Li 'et al.' ) <doi:10.1111/j.1538-4632.2007.00708.x>, local 'Moran's I', 'Gearys C' ('Anselin' 1995) <doi:10.1111/j.1538-4632.1995.tb00338.x> and 'Getis/Ord' G ('Ord' and 'Getis' 1995) <doi:10.1111/j.1538-4632.1995.tb00912.x>, 'saddlepoint' approximations ('Tiefelsdorf' 2002) <doi:10.1111/j.1538-4632.2002.tb01084.x> and exact tests for global and local 'Moran's I' ('Bivand et al.' 2009) <doi:10.1016/j.csda.2008.07.021> and 'LOSH' local indicators of spatial heteroscedasticity ('Ord' and 'Getis') <doi:10.1007/s00168-011-0492-y>. The implementation of most of these measures is described in 'Bivand' and 'Wong' (2018) <doi:10.1007/s11749-018-0599-x>, with further extensions in 'Bivand' (2022) <doi:10.1111/gean.12319>. 'Lagrange' multiplier tests for spatial dependence in linear models are provided ('Anselin et al'. 1996) <doi:10.1016/0166-0462(95)02111-6>, as are 'Rao' score tests for hypothesised spatial 'Durbin' models based on linear models ('Koley' and 'Bera' 2023) <doi:10.1080/17421772.2023.2256810>. A local indicators for categorical data (LICD) implementation based on 'Carrer et al.' (2021) <doi:10.1016/j.jas.2020.105306> and 'Bivand et al.' (2017) <doi:10.1016/j.spasta.2017.03.003> was added in 1.3-7. From 'spdep' and 'spatialreg' versions >= 1.2-1, the model fitting functions previously present in this package are defunct in 'spdep' and may be found in 'spatialreg'.

Maintained by Roger Bivand. Last updated 19 days ago.

spatial-autocorrelationspatial-dependencespatial-weights

3.3 match 131 stars 16.62 score 6.0k scripts 107 dependents

hadley

proto:Prototype Object-Based Programming

An object oriented system using object-based, also called prototype-based, rather than class-based object oriented ideas.

Maintained by Hadley Wickham. Last updated 8 years ago.

3.1 match 12 stars 11.65 score 366 scripts 110 dependents

husson

SensoMineR:Sensory Data Analysis

Statistical Methods to Analyse Sensory Data. SensoMineR: A package for sensory data analysis. S. Le and F. Husson (2008).

Maintained by Francois Husson. Last updated 1 years ago.

6.0 match 5.72 score 108 scripts 3 dependents

jienagu

flashCard:Create a Flash Card

Create a flip over style Flash Card with desired data frame for Shiny application.

Maintained by Jiena McLellan. Last updated 3 years ago.

5.9 match 36 stars 5.40 score 14 scripts

cran

bayesm:Bayesian Inference for Marketing/Micro-Econometrics

Covers many important models used in marketing and micro-econometrics applications. The package includes: Bayes Regression (univariate or multivariate dep var), Bayes Seemingly Unrelated Regression (SUR), Binary and Ordinal Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP), Multivariate Probit, Negative Binomial (Poisson) Regression, Multivariate Mixtures of Normals (including clustering), Dirichlet Process Prior Density Estimation with normal base, Hierarchical Linear Models with normal prior and covariates, Hierarchical Linear Models with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates, Hierarchical Negative Binomial Regression Models, Bayesian analysis of choice-based conjoint data, Bayesian treatment of linear instrumental variables models, Analysis of Multivariate Ordinal survey data with scale usage heterogeneity (as in Rossi et al, JASA (01)), Bayesian Analysis of Aggregate Random Coefficient Logit Models as in BLP (see Jiang, Manchanda, Rossi 2009) For further reference, consult our book, Bayesian Statistics and Marketing by Rossi, Allenby and McCulloch (Wiley first edition 2005 and second forthcoming) and Bayesian Non- and Semi-Parametric Methods and Applications (Princeton U Press 2014).

Maintained by Peter Rossi. Last updated 1 years ago.

openblascpp

3.8 match 20 stars 8.20 score 322 scripts 43 dependents

aiorazabala

qmethod:Analysis of Subjective Perspectives Using Q Methodology

Analysis of Q methodology, used to identify distinct perspectives existing within a group. This methodology is used across social, health and environmental sciences to understand diversity of attitudes, discourses, or decision-making styles (for more information, see <https://qmethod.org/>). A single function runs the full analysis. Each step can be run separately using the corresponding functions: for automatic flagging of Q-sorts (manual flagging is optional), for statement scores, for distinguishing and consensus statements, and for general characteristics of the factors. The package allows to choose either principal components or centroid factor extraction, manual or automatic flagging, a number of mathematical methods for rotation (or none), and a number of correlation coefficients for the initial correlation matrix, among many other options. Additional functions are available to import and export data (from raw *.CSV, 'HTMLQ' and 'FlashQ' *.CSV, 'PQMethod' *.DAT and 'easy-htmlq' *.JSON files), to print and plot, to import raw data from individual *.CSV files, and to make printable cards. The package also offers functions to print Q cards and to generate Q distributions for study administration. See further details in the package documentation, and in the web pages below, which include a cookbook, guidelines for more advanced analysis (how to perform manual flagging or change the sign of factors), data management, and a graphical user interface (GUI) for online and offline use.

Maintained by Aiora Zabala. Last updated 1 years ago.

4.6 match 38 stars 6.03 score 47 scripts

carloscinelli

benford.analysis:Benford Analysis for Data Validation and Forensic Analytics

Provides tools that make it easier to validate data using Benford's Law.

Maintained by Carlos Cinelli. Last updated 6 years ago.

3.8 match 62 stars 5.66 score 74 scripts

alanarnholt

PASWR:Probability and Statistics with R

Functions and data sets for the text Probability and Statistics with R.

Maintained by Alan T. Arnholt. Last updated 3 years ago.

3.8 match 2 stars 4.70 score 241 scripts

alanarnholt

PASWR2:Probability and Statistics with R, Second Edition

Functions and data sets for the text Probability and Statistics with R, Second Edition.

Maintained by Alan T. Arnholt. Last updated 3 years ago.

3.8 match 1 stars 4.24 score 260 scripts

rinterface

argonDash:Argon Shiny Dashboard Template

Create awesome 'Bootstrap 4' dashboards powered by 'Argon'.

Maintained by David Granjon. Last updated 2 months ago.

argon-dashboard-templatebootstrap4shinyshiny-apps

1.8 match 138 stars 6.47 score 72 scripts 2 dependents

glsnow

blockrand:Randomization for Block Random Clinical Trials

Create randomizations for block random clinical trials. Can also produce a pdf file of randomization cards.

Maintained by Greg Snow. Last updated 5 years ago.

2.3 match 2 stars 3.60 score 67 scripts 1 dependents

trevorld

pnpmisc:Utilities for Print-and-Play Board Games

Utilities for print-and-play board games.

Maintained by Trevor L. Davis. Last updated 13 days ago.

print-and-play

1.8 match 3.02 score 1 dependents

christopherkenny

royale:Clash Royale API

R interface to the official API for Clash Royale <https://developer.clashroyale.com/#/>.

Maintained by Christopher T. Kenny. Last updated 1 years ago.

2.0 match 1.70 score 4 scripts

jdench

rSHAPE:Simulated Haploid Asexual Population Evolution

In silico experimental evolution offers a cost-and-time effective means to test evolutionary hypotheses. Existing evolutionary simulation tools focus on simulations in a limited experimental framework, and tend to report on only the results presumed of interest by the tools designer. The R-package for Simulated Haploid Asexual Population Evolution ('rSHAPE') addresses these concerns by implementing a robust simulation framework that outputs complete population demographic and genomic information for in silico evolving communities. Allowing more than 60 parameters to be specified, 'rSHAPE' simulates evolution across discrete time-steps for an evolving community of haploid asexual populations with binary state genomes. These settings are for the current state of 'rSHAPE' and future steps will be to increase the breadth of evolutionary conditions permitted. At present, most effort was placed into permitting varied growth models to be simulated (such as constant size, exponential growth, and logistic growth) as well as various fitness landscape models to reflect the evolutionary landscape (e.g.: Additive, House of Cards - Stuart Kauffman and Simon Levin (1987) <doi:10.1016/S0022-5193(87)80029-2>, NK - Stuart A. Kauffman and Edward D. Weinberger (1989) <doi:10.1016/S0022-5193(89)80019-0>, Rough Mount Fuji - Neidhart, Johannes and Szendro, Ivan G and Krug, Joachim (2014) <doi:10.1534/genetics.114.167668>). This package includes numerous functions though users will only need defineSHAPE(), runSHAPE(), shapeExperiment() and summariseExperiment(). All other functions are called by these main functions and are likely only to be on interest for someone wishing to develop 'rSHAPE'. Simulation results will be stored in files which are exported to the directory referenced by the shape_workDir option (defaults to tempdir() but do change this by passing a folderpath argument for workDir when calling defineSHAPE() if you plan to make use of your results beyond your current session). 'rSHAPE' will generate numerous replicate simulations for your defined range of experimental parameters. The experiment will be built under the experimental working directory (i.e.: referenced by the option shape_workDir set using defineSHAPE() ) where individual replicate simulation results will be stored as well as processed results which I have made in an effort to facilitate analyses by automating collection and processing of the potentially thousands of files which will be created. On that note, 'rSHAPE' implements a robust and flexible framework with highly detailed output at the cost of computational efficiency and potentially requiring significant disk space (generally gigabytes but up to tera-bytes for very large simulation efforts). So, while 'rSHAPE' offers a single framework in which we can simulate evolution and directly compare the impacts of a wide range of parameters, it is not as quick to run as other in silico simulation tools which focus on a single scenario with limited output. There you have it, 'rSHAPE' offers you a less restrictive in silico evolutionary playground than other tools and I hope you enjoy testing your hypotheses.

Maintained by Jonathan Dench. Last updated 6 years ago.

0.5 match 1.00 score