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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"
        },
        {
            "name": "R-prophet",
            "description": "Automatic forecasting procedure"
        },
        {
            "name": "R-PROreg",
            "description": "Patient reported outcomes regression analysis"
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        {
            "name": "R-proto",
            "description": "Prototype object-based programming"
        },
        {
            "name": "R-protolite",
            "description": "Highly optimized protocol buffer serializers"
        },
        {
            "name": "R-proxy",
            "description": "Distance and Similarity Measures"
        },
        {
            "name": "R-proxyC",
            "description": "Computes proximity between rows or columns of large matrices efficiently in C++"
        },
        {
            "name": "R-PRROC",
            "description": "Precision-recall and ROC curves for weighted and unweighted data"
        },
        {
            "name": "R-PRSPGx",
            "description": "Construct PGx PRS"
        },
        {
            "name": "R-prt",
            "description": "Tabular data backed by partitioned fst files"
        },
        {
            "name": "R-PRTree",
            "description": "Probabilistic Regression Trees"
        },
        {
            "name": "R-pryr",
            "description": "Pry open the covers of R"
        },
        {
            "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"
        },
        {
            "name": "R-PSCBS",
            "description": "Analysis of parent-specific DNA copy numbers"
        },
        {
            "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"
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        {
            "name": "R-psfmi",
            "description": "Prediction model pooling, selection and performance evaluation across multiply imputed datasets"
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            "name": "R-psgp",
            "description": "Projected spatial Gaussian process methods"
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        {
            "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"
        },
        {
            "name": "R-pspline",
            "description": "Penalized Smoothing Splines"
        },
        {
            "name": "R-psqn",
            "description": "Partially Separable Quasi-Newton"
        },
        {
            "name": "R-PStrata",
            "description": "Principal stratification analysis in R"
        },
        {
            "name": "R-psych",
            "description": "Procedures for psychological, psychometric and personality research"
        },
        {
            "name": "R-psychotools",
            "description": "Psychometric modelling infrastructure"
        },
        {
            "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"
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        {
            "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."
        },
        {
            "name": "R-PUlasso",
            "description": "High-dimensional variable selection with presence-only data"
        },
        {
            "name": "R-puniform",
            "description": "Meta-analysis methods correcting for publication bias"
        },
        {
            "name": "R-purrr",
            "description": "Functional programming tools"
        },
        {
            "name": "R-purrrlyr",
            "description": "Tools at the intersection of purrr and dplyr"
        },
        {
            "name": "R-Pursuit",
            "description": "Projection pursuit"
        },
        {
            "name": "R-pvclust",
            "description": "Hierarchical clustering with p-values via multiscale bootstrap resampling"
        },
        {
            "name": "R-PVR",
            "description": "Phylogenetic eigenvectors regression and phylogentic signal-representation curve"
        },
        {
            "name": "R-pwalign",
            "description": "Perform pairwise sequence alignments"
        },
        {
            "name": "R-PWEXP",
            "description": "Piece-wise exponential distribution prediction model"
        },
        {
            "name": "R-pwr",
            "description": "Basic functions for power analysis"
        },
        {
            "name": "R-pyinit",
            "description": "Pena–Yohai initial estimator for robust s-regression"
        },
        {
            "name": "R-pzfx",
            "description": "Read and write GraphPad Prism files"
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}