All packages

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praatpicture — 1.2.0

'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 — 1.1.2

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 — 1.0.0

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 — 3.0.10

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 — 0.1-11

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

PredPsych — 0.4

Predictive Approaches in Psychology

predReliability — 0.1.0

Estimates Reliability of Individual Supervised Learning Predictions

predRupdate — 0.2.0

Prediction Model Validation and Updating

PredTest — 0.1.0

Preparing Data For, and Calculating the Prediction Test

predtools — 0.0.3

Prediction Model Tools

predtoolsTS — 0.1.1

Time Series Prediction Tools

pref — 0.4.0

Preference Voting with Explanatory Graphics

prefeR — 0.1.3

R Package for Pairwise Preference Elicitation

preferably — 0.4.1

A 'pkgdown' Template

preference — 1.1.6

2-Stage Preference Trial Design and Analysis

prefio — 0.1.1

Structures for Preference Data

prefmod — 0.8-36

Utilities to Fit Paired Comparison Models for Preferences

PreKnitPostHTMLRender — 0.1.0

Pre-Knitting Processing and Post HTML-Rendering Processing

PReMiuM — 3.2.13

Dirichlet Process Bayesian Clustering, Profile Regression

prenoms — 0.0.1

Names Given to Babies in Quebec Between 1980 and 2020

prepdat — 1.0.8

Preparing Experimental Data for Statistical Analysis

pRepDesigns — 1.2.0

Partially Replicated (p-Rep) Designs

prepplot — 1.0-1

Prepare Figure Region for Base Graphics

PreProcess — 3.1.7

Basic Functions for Pre-Processing Microarrays

PreProcessing — 0.1.0

Various Preprocessing Transformations of Numeric Data Matrices

PreProcessRecordLinkage — 1.0.1

Preprocessing Record Linkage

PREPShiny — 0.1.0

Interactive Document for Preprocessing the Dataset

preputils — 1.0.3

Utilities for Preparation of Data Analysis

prereg — 0.6.0

R Markdown Templates to Preregister Scientific Studies

preregr — 0.2.9

Specify (Pre)Registrations and Export Them Human- And Machine-Readably

PresenceAbsence — 1.1.11

Presence-Absence Model Evaluation

presens — 2.1.0

Interface for PreSens Fiber Optic Data

presenter — 0.1.2

Present Data with Style

presentes — 0.1.0

Registry of Victims of State Terrorism in Argentina

preseqR — 4.0.0

Predicting Species Accumulation Curves

PResiduals — 1.0-1

Probability-Scale Residuals and Residual Correlations

presize — 0.3.7

Precision Based Sample Size Calculation

presmTP — 1.1.0

Methods for Transition Probabilities

PressPurt — 1.0.2

Indeterminacy of Networks via Press Perturbations

pressuRe — 0.2.4

Imports, Processes, and Visualizes Biomechanical Pressure Data

pretest — 0.2

A Novel Approach to Predictive Accuracy Testing in Nested Environments

prettifyAddins — 2.6.1

'RStudio' Addins to Prettify 'JavaScript', 'C++', 'Python', and More

prettyB — 0.2.2

Pretty Base Graphics

prettycode — 1.1.0

Pretty Print R Code in the Terminal

PrettyCols — 1.1.0

Pretty Colour Palettes

prettydoc — 0.4.1

Creating Pretty Documents from R Markdown

prettyglm — 1.0.1

Pretty Summaries of Generalized Linear Model Coefficients

prettyGraphs — 2.1.6

Publication-Quality Graphics

prettymapr — 0.2.5

Scale Bar, North Arrow, and Pretty Margins in R

prettyR — 2.2-3

Pretty Descriptive Stats

prettyunits — 1.2.0

Pretty, Human Readable Formatting of Quantities

prevalence — 0.4.1

Tools for Prevalence Assessment Studies

prevederer — 0.0.1

Wrapper for the 'Prevedere' API

preventr — 0.10.0

An Implementation of the AHA PREVENT Equations

previsionio — 11.7.0

'Prevision.io' R SDK

PrevMap — 1.5.4

Geostatistical Modelling of Spatially Referenced Prevalence Data

prevR — 5.0.0

Estimating Regional Trends of a Prevalence from a DHS and Similar Surveys

prevtoinc — 0.12.0

Prevalence to Incidence Calculations for Point-Prevalence Studies in a Nosocomial Setting

pRF — 1.2

Permutation Significance for Random Forests

PriceIndices — 0.2.1

Calculating Bilateral and Multilateral Price Indexes

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