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"name": "R-proffer",
"description": "Profile R code and visualize with Pprof"
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"name": "R-profile",
"description": "Read, manipulate and write profiler data"
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"name": "R-profileModel",
"description": "Profiling inference functions for various model classes"
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"name": "R-profmem",
"description": "Simple memory profiling for R"
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"name": "R-profvis",
"description": "Interactive visualizations for profiling R code"
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"name": "R-progress",
"description": "Progress bar in your R terminal"
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"name": "R-progressr",
"description": "Inclusive, unifying API for progress updates"
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"name": "R-PROJ",
"description": "Generic coordinate system transformations using PROJ"
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"name": "R-proj4",
"description": "Simple R interface to the PROJ.4 cartographic projections library"
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"name": "R-projpred",
"description": "Projection predictive feature selection"
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{
"name": "R-prolsirm",
"description": "Procrustes matching for latent space item response model"
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{
"name": "R-promises",
"description": "Abstractions for promise-based asynchronous programming"
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"name": "R-propagate",
"description": "Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation"
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"name": "R-prophet",
"description": "Automatic forecasting procedure"
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{
"name": "R-PROreg",
"description": "Patient reported outcomes regression analysis"
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"name": "R-proto",
"description": "Prototype object-based programming"
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"name": "R-protolite",
"description": "Highly optimized protocol buffer serializers"
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"name": "R-proxy",
"description": "Distance and Similarity Measures"
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"name": "R-proxyC",
"description": "Computes proximity between rows or columns of large matrices efficiently in C++"
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{
"name": "R-PRROC",
"description": "Precision-recall and ROC curves for weighted and unweighted data"
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{
"name": "R-PRSPGx",
"description": "Construct PGx PRS"
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{
"name": "R-prt",
"description": "Tabular data backed by partitioned fst files"
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{
"name": "R-PRTree",
"description": "Probabilistic Regression Trees"
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"name": "R-pryr",
"description": "Pry open the covers of R"
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"name": "R-ps",
"description": "R package to query, list and manipulate system processes"
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"name": "R-psborrow",
"description": "Bayesian dynamic borrowing with propensity score"
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"name": "R-PSCBS",
"description": "Analysis of parent-specific DNA copy numbers"
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{
"name": "R-pscl",
"description": "Political Science Computational Laboratory"
},
{
"name": "R-psd",
"description": "Adaptive sine-multitaper power spectral density and cross-spectrum estimation"
},
{
"name": "R-PSDistr",
"description": "Distributions derived from normal distribution"
},
{
"name": "R-psdr",
"description": "Use time series to generate and compare power spectral density"
},
{
"name": "R-psfmi",
"description": "Prediction model pooling, selection and performance evaluation across multiply imputed datasets"
},
{
"name": "R-psgp",
"description": "Projected spatial Gaussian process methods"
},
{
"name": "R-psica",
"description": "Decision tree analysis for probabilistic subgroup identification with multiple treatments"
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{
"name": "R-pso",
"description": "Particle Swarm Optimization"
},
{
"name": "R-psp",
"description": "Parameter Space Partitioning MCMC for global model evaluation"
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{
"name": "R-pspline",
"description": "Penalized Smoothing Splines"
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{
"name": "R-psqn",
"description": "Partially Separable Quasi-Newton"
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{
"name": "R-PStrata",
"description": "Principal stratification analysis in R"
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{
"name": "R-psych",
"description": "Procedures for psychological, psychometric and personality research"
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{
"name": "R-psychotools",
"description": "Psychometric modelling infrastructure"
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{
"name": "R-psychotree",
"description": "Recursive partitioning based on psychometric models"
},
{
"name": "R-psychTools",
"description": "Tools to accompany the R-psych package for psychological research"
},
{
"name": "R-ptf",
"description": "Probit Tensor Factorization"
},
{
"name": "R-ptw",
"description": "Parametric Time Warping"
},
{
"name": "R-PublicationBias",
"description": "Sensitivity analysis for publication bias in meta-analyses"
},
{
"name": "R-publipha",
"description": "Bayesian meta-analysis with publications bias and p-hacking"
},
{
"name": "R-Publish",
"description": "Format output of various routines in a suitable way for reports and publication."
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{
"name": "R-PUlasso",
"description": "High-dimensional variable selection with presence-only data"
}
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}