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"description": "Processing of model parameters"
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"name": "R-ParetoPosStable",
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"name": "R-parglm",
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"description": "Common API to modeling and analysis functions"
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"description": "Periodic autoregressive time series models"
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"description": "Computational toolbox for recursive partitioning"
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"description": "Package for analysis of space-time ecological series"
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"description": "Probability and Statistics with R"
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"description": "Parameterized unit testing"
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"description": "Adding progress bar to *apply functions"
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"description": "Interface to MPI"
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"description": "ScaLAPACK/PBLAS/BLACS/LAPACK library for use with pbdR"
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"name": "R-pbdZMQ",
"description": "Interface to ZeroMQ"
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"name": "R-pbivnorm",
"description": "Vectorized bivariate normal CDF"
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"name": "R-pbkrtest",
"description": "Parametric Bootstrap, Kenward–Roger and Satterthwaite based methods for test in mixed models"
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"name": "R-pbmcapply",
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"name": "R-pBrackets",
"description": "Plot brackets"
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"name": "R-pbs",
"description": "Periodic b-splines"
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"name": "R-pbv",
"description": "Probabilities for Bivariate Normal distribution"
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"description": "Fast principal component analysis for outlier detection"
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"name": "R-pcalg",
"description": "Methods for graphical models and causal inference"
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"description": "Collection of PCA methods"
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"description": "Robust PCA by Projection Pursuit"
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"name": "R-pcgen",
"description": "Reconstruction of causal networks for data with random genetic effects"
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{
"name": "R-pchc",
"description": "Bayesian network learning with the PCHC"
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{
"name": "R-PCICt",
"description": "Implementation of POSIXct work-alike for 365- and 360-day calendars"
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{
"name": "R-pcLasso",
"description": "Principal Components Lasso"
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{
"name": "R-pcnetmeta",
"description": "Bayesian arm-based network meta-analysis for datasets with binary, continuous and count outcomes"
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{
"name": "R-PCovR",
"description": "Principal covariates regression"
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{
"name": "R-pcse",
"description": "Panel-corrected standard error estimation in R"
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