This package is considered a duplicate. The official version of this package is found at:https://jpritikin.r-universe.dev/pcFactorStan

Package: pcFactorStan 1.5.4

Joshua N. Pritikin

pcFactorStan: Stan Models for the Paired Comparison Factor Model

Provides convenience functions and pre-programmed Stan models related to the paired comparison factor model. Its purpose is to make fitting paired comparison data using Stan easy. This package is described in Pritikin (2020) <doi:10.1016/j.heliyon.2020.e04821>.

Authors:Joshua N. Pritikin [aut, cre], Daniel C. Furr [ctb], Trustees of Columbia University [cph]

pcFactorStan_1.5.4.tar.gz
pcFactorStan_1.5.4.zip(r-4.7-x86_64)pcFactorStan_1.5.4.zip(r-4.7-arm64)pcFactorStan_1.5.4.zip(r-4.6-x86_64)pcFactorStan_1.5.4.zip(r-4.6-arm64)
pcFactorStan_1.5.4.tar.gz(r-4.7-arm64)pcFactorStan_1.5.4.tar.gz(r-4.7-x86_64)pcFactorStan_1.5.4.tar.gz(r-4.6-arm64)pcFactorStan_1.5.4.tar.gz(r-4.6-x86_64)
pcFactorStan_1.5.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
pcFactorStan/json (API)

# Install 'pcFactorStan' in R:

install.packages('pcFactorStan', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jpritikin/pcfactorstan/issues

Uses libs:

onetbb– Parallelism library for C++
c++– GNU Standard C++ Library v3

Datasets:

phyActFlowPropensity - Physical activity flow propensity

On CRAN:

onetbb cpp

2.70 score 523 downloads 25 exports 56 dependencies

Last updated from:ceeed125c3. Checks:8 NOTE, 2 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	NOTE	604
linux-devel-x86_64	NOTE	705
source / vignettes	OK	847
linux-release-arm64	NOTE	674
linux-release-x86_64	NOTE	532
windows-devel-arm64	NOTE	738
windows-devel-x86_64	NOTE	952
windows-release-arm64	NOTE	711
windows-release-x86_64	NOTE	991
wasm-release	OK	490

Exports:calibrateItems cmp_probs filterGraph findModel generateCovItems generateFactorItems generateItem generateSingleFactorItems itemModelExplorer normalizeData outlierTable parDistributionCustom parDistributionFor parInterval pcStan prepCleanData prepData prepFactorModel prepSingleFactorModel responseCurve roundRobinGraph toLoo twoLevelGraph unfactor withoutIndex

Dependencies:abind backports BH callr checkmate cli cpp11 desc distributional farver generics ggplot2 glue gridExtra gtable igraph inline isoband labeling lattice lifecycle loo magrittr Matrix matrixStats mvtnorm numDeriv otel pillar pkgbuild pkgconfig plyr posterior processx ps QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel reshape2 rlang rstan rstantools S7 scales StanHeaders stringi stringr tensorA tibble utf8 vctrs viridisLite withr

A brief manual

Rendered frommanual.Rmdusingknitr::rmarkdown

Last update: 2020-09-15
Started: 2019-07-23

Citation

Readme and manuals

Help Manual

Help page	Topics
Stan Models for the Pairwise Comparison Factor Model	pcFactorStan-package pcFactorStan
Determine the optimal scale constant for a set of items	calibrateItems
Item response function for pairwise comparisons	cmp_probs
Filter graph to remove vertices that are not well connected	filterGraph
Given a model name, return stanmodel object	findModel
Generate paired comparison data with random correlations between items	generateCovItems
Generate paired comparison data for a factor model	generateFactorItems
Generate paired comparison data for one or more items given absolute latent scores	generateItem
Generate paired comparison data with a common factor that accounts for some proportion of the variance	generateSingleFactorItems
A Shiny app to experiment with the item response model	itemModelExplorer
Normalize data according to a canonical order	normalizeData
List observations with Pareto values larger than a given threshold	outlierTable
Produce data suitable for plotting parameter distributions	parDistributionCustom parDistributionFor
Produce data suitable for plotting parameter estimates	parInterval
Fit a paired comparison Stan model	pcStan
Physical activity flow propensity	phyActFlowPropensity
Transforms data into a form tailored for efficient evaluation by Stan	prepCleanData
Transforms data into a form tailored for efficient evaluation by Stan	prepData
Specify a factor model	prepFactorModel
Specify a single factor model	prepSingleFactorModel
Produce data suitable for plotting item response curves	responseCurve
Create an edge list with round-robin connectivity	roundRobinGraph
Compute approximate leave-one-out (LOO) cross-validation for Bayesian models using Pareto smoothed importance sampling (PSIS)	toLoo
Create an edge list with a random two level connectivity	twoLevelGraph
Turn a factor back into a vector of integers	unfactor
Remove the array indexing from a parameter name	withoutIndex

Package: pcFactorStan 1.5.4

pcFactorStan: Stan Models for the Paired Comparison Factor Model

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)