All packages

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powerLATE — 0.1.2

Generalized Power Analysis for LATE

poweRlaw — 0.80.0

Analysis of Heavy Tailed Distributions

powerly — 1.8.6

Sample Size Analysis for Psychological Networks and More

powerMediation — 0.3.4

Power/Sample Size Calculation for Mediation Analysis

powerNLSEM — 0.1.2

Simulation-Based Power Estimation (MSPE) for Nonlinear SEM

PowerNormal — 1.2.0

Power Normal Distribution

powerpkg — 1.6

Power Analyses for the Affected Sib Pair and the TDT Design

powerPLS — 0.2.0

Power Analysis for PLS Classification

PowerSDI — 1.0.0

Calculate Standardised Drought Indices Using NASA POWER Data

powerSurvEpi — 0.1.3

Power and Sample Size Calculation for Survival Analysis of Epidemiological Studies

powertools — 0.1.2

Power and Sample Size Tools

PowerTOST — 1.5-6

Power and Sample Size for (Bio)Equivalence Studies

PowerUpR — 1.1.0

Power Analysis Tools for Multilevel Randomized Experiments

powRICLPM — 0.2.1

Perform Power Analysis for the RI-CLPM and STARTS Model

PP — 0.6.3-11

Person Parameter Estimation

PPbigdata — 1.0.0

Projection Pursuit for Big Data Based on Data Nuggets

pPCA — 1.1

Partial Principal Component Analysis of Partitioned Large Sparse Matrices

ppcc — 1.2

Probability Plot Correlation Coefficient Test

PPCDT — 0.2.0

An Optimal Subset Selection for Distributed Hypothesis Testing

PPCI — 0.1.5

Projection Pursuit for Cluster Identification

ppclust — 1.1.0.1

Probabilistic and Possibilistic Cluster Analysis

ppcor — 1.1

Partial and Semi-Partial (Part) Correlation

ppcSpatial — 0.3.0

Spatial Analysis of Pakistan Population Census

ppdiag — 0.1.1

Diagnosis and Visualizations Tools for Temporal Point Processes

ppendemic — 0.1.8

A Glimpse at the Diversity of Peru's Endemic Plants

PPforest — 0.1.3

Projection Pursuit Classification Forest

ppgam — 1.0.2

Generalised Additive Point Process Models

ppgm — 1.0.3

PaleoPhyloGeographic Modeling of Climate Niches and Species Distributions

ppgmmga — 1.3

Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms

ppitables — 0.5.5

Lookup Tables to Generate Poverty Likelihoods and Rates using the Poverty Probability Index (PPI)

PPLasso — 2.0

Prognostic Predictive Lasso for Biomarker Selection

ppmf — 0.1.3

Read Census Privacy Protected Microdata Files

ppmHR — 1.0

Privacy-Protecting Hazard Ratio Estimation in Distributed Data Networks

PPMiss — 0.1.1

Copula-Based Estimator for Long-Range Dependent Processes under Missing Data

ppmlasso — 1.4

Point Process Models with LASSO-Type Penalties

PPMR — 1.0

Probabilistic Two Sample Mendelian Randomization

ppmSuite — 0.3.4

A Collection of Models that Employ Product Partition Distributions as a Prior on Partitions

PPQplan — 1.1.0

Process Performance Qualification (PPQ) Plans in Chemistry, Manufacturing and Controls (CMC) Statistical Analysis

ppRank — 0.1.1

Classification of Algorithms

ppRep — 0.42.3

Analysis of Replication Studies using Power Priors

PPRL — 0.3.8

Privacy Preserving Record Linkage

pps — 1.0

PPS Sampling

ppsbm — 0.2.2

Clustering in Longitudinal Networks

ppseq — 0.2.5

Design Clinical Trials using Sequential Predictive Probability Monitoring

PPSFS — 0.1.0

Partial Profile Score Feature Selection in High-Dimensional Generalized Linear Interaction Models

ppsr — 0.0.5

Predictive Power Score

PPTcirc — 0.2.3

Projected Polya Tree for Circular Data

PPtreeregViz — 2.0.5

Projection Pursuit Regression Tree Visualization

PPtreeViz — 2.0.4

Projection Pursuit Classification Tree Visualization

pqantimalarials — 0.2

web tool for estimating under-five deaths caused by poor-quality antimalarials in sub-Saharan Africa

pql — 0.1.0

A Partitioned Quasi-Likelihood for Distributed Statistical Inference

PQLseq — 1.2.1

Efficient Mixed Model Analysis of Count Data in Large-Scale Genomic Sequencing Studies

pqrBayes — 1.0.2

Bayesian Penalized Quantile Regression

pqrfe — 1.1

Penalized Quantile Regression with Fixed Effects

PRA — 0.3.0

Project Risk Analysis

praatpicture — 1.3.0

'Praat Picture' Style Plots of Acoustic Data

prabclus — 2.3-4

Functions for Clustering and Testing of Presence-Absence, Abundance and Multilocus Genetic Data

pracma — 2.4.4

Practical Numerical Math Functions

pracpac — 0.2.0

Practical 'R' Packaging in 'Docker'

PracticalEquiDesign — 0.0.3

Design of Practical Equivalence Trials

practicalSigni — 0.1.2

Practical Significance Ranking of Regressors and Exact t Density

PracTools — 1.5

Designing and Weighting Survey Samples

prais — 1.1.3

Prais-Winsten Estimator for AR(1) Serial Correlation

praise — 1.0.0

Praise Users

PRANA — 1.0.6

Pseudo-Value Regression Approach for Network Analysis (PRANA)

praznik — 11.0.0

Tools for Information-Based Feature Selection and Scoring

prcbench — 1.1.8

Testing Workbench for Precision-Recall Curves

prclust — 1.3

Penalized Regression-Based Clustering Method

prcr — 0.2.1

Person-Centered Analysis

PRDA — 1.0.0

Conduct a Prospective or Retrospective Design Analysis

pre — 1.0.7

Prediction Rule Ensembles

PRECAST — 1.6.5

Embedding and Clustering with Alignment for Spatial Datasets

precintcon — 2.3.0

Precipitation Intensity, Concentration and Anomaly Analysis

pRecipe — 3.0.1-3

Precipitation R Recipes

precisely — 0.1.2

Estimate Sample Size Based on Precision Rather than Power

precisePlacement — 0.1.0

Suite of Functions to Help Get Plot Elements Exactly Where You Want Them

PreciseSums — 0.7

Accurate Floating Point Sums and Products

precmed — 1.1.0

Precision Medicine

precommit — 0.4.3

Pre-Commit Hooks

precondition — 0.1.0

Lightweight Precondition, Postcondition, and Sanity Checks

precrec — 0.14.4

Calculate Accurate Precision-Recall and ROC (Receiver Operator Characteristics) Curves

PredCRG — 1.0.2

Computational Prediction of Proteins Encoded by Circadian Genes

predfairness — 0.1.0

Discrimination Mitigation for Machine Learning Models

predhy — 2.1.1

Genomic Prediction of Hybrid Performance

predhy.GUI — 2.0.1

Genomic Prediction of Hybrid Performance with Graphical User Interface

predict3d — 0.1.5

Draw Three Dimensional Predict Plot Using Package 'rgl'

PredictABEL — 1.2-4

Assessment of Risk Prediction Models

prediction — 0.3.18

Tidy, Type-Safe 'prediction()' Methods

predictionInterval — 1.0.0

Prediction Interval Functions for Assessing Replication Study Results

PredictionR — 1.0-12

Prediction for Future Data from any Continuous Distribution

predictMe — 0.1

Visualize Individual Prediction Performance

predictmeans — 1.1.0

Predicted Means for Linear and Semiparametric Models

predictNMB — 0.2.1

Evaluate Clinical Prediction Models by Net Monetary Benefit

predictoR — 4.1.1

Predictive Data Analysis System

PredictorSelect — 0.1.0

Out-of-Sample Predictability in Predictive Regressions with Many Predictor Candidates

predictrace — 2.0.1

Predict the Race and Gender of a Given Name Using Census and Social Security Administration Data

predicts — 0.1-17

Spatial Prediction Tools

predieval — 0.1.1

Assessing Performance of Prediction Models for Predicting Patient-Level Treatment Benefit

predint — 2.2.1

Prediction Intervals

predkmeans — 0.1.1

Covariate Adaptive Clustering

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