All packages

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plotprotein — 1.0

Development of Visualization Tools for Protein Sequence

plotrix — 3.8-4

Various Plotting Functions

plotROC — 2.3.1

Generate Useful ROC Curve Charts for Print and Interactive Use

plotscale — 0.1.6

Scale Graphics Devices Using Plot Dimensions

plotscaper — 0.2.4

Explore Your Data with Interactive Figures

plotSEMM — 2.4

Graphing Nonlinear Relations Among Latent Variables from Structural Equation Mixture Models

plotthis — 0.3.6

High-Level Plotting Built Upon 'ggplot2' and Other Plotting Packages

PlotTools — 0.3.1

Add Continuous Legends to Plots

plotwidgets — 0.5.1

Spider Plots, ROC Curves, Pie Charts and More for Use in Other Plots

plpoisson — 0.3.1

Prediction Limits for Poisson Distribution

PLreg — 0.4.1

Power Logit Regression for Modeling Bounded Data

PLRModels — 1.4

Statistical Inference in Partial Linear Regression Models

pls — 2.8-5

Partial Least Squares and Principal Component Regression

plsdepot — 0.2.0

Partial Least Squares (PLS) Data Analysis Methods

plsdof — 0.3-2

Degrees of Freedom and Statistical Inference for Partial Least Squares Regression

plsgenomics — 1.5-3

PLS Analyses for Genomics

PLSiMCpp — 1.0.4

Methods for Partial Linear Single Index Model

plsmmLasso — 1.1.0

Variable Selection and Inference for Partial Semiparametric Linear Mixed-Effects Model

plsmod — 1.0.0

Model Wrappers for Projection Methods

plsmselect — 0.2.0

Linear and Smooth Predictor Modelling with Penalisation and Variable Selection

plspm — 0.5.1

Partial Least Squares Path Modeling (PLS-PM)

plsRbeta — 0.3.0

Partial Least Squares Regression for Beta Regression Models

plsRcox — 1.7.7

Partial Least Squares Regression for Cox Models and Related Techniques

plsRglm — 1.5.1

Partial Least Squares Regression for Generalized Linear Models

plsVarSel — 0.9.12

Variable Selection in Partial Least Squares

pltesim — 1.0

Simulate Probabilistic Long-Term Effects in Models with Temporal Dependence

plu — 0.3.0

Dynamically Pluralize Phrases

plugdensity — 0.8-5

Plug-in Kernel Density Estimation

plumber — 1.2.2

An API Generator for R

plumberDeploy — 0.2.1

Plumber Deployment

plumbertableau — 0.1.1

Turn 'Plumber' APIs into 'Tableau' Extensions

plumbr — 0.6.10

Mutable and Dynamic Data Models

plume — 0.2.5

A Simple Author Handler for Scientific Writing

pluscode — 0.1.0

Encoder for Google 'Pluscodes'

plusCode2 — 0.1.0

Coordinates to 'Plus Code' Conversion Tool

plutor — 0.1.0

Useful Functions for Visualization

plyr — 1.8.9

Tools for Splitting, Applying and Combining Data

pm3 — 0.2.0

Propensity Score Matching for Unordered 3-Group Data

PMA — 1.2-4

Penalized Multivariate Analysis

PMAPscore — 0.1.1

Identify Prognosis-Related Pathways Altered by Somatic Mutation

pmartR — 2.4.6

Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data

pmc — 1.0.6

Phylogenetic Monte Carlo

pmcalibration — 0.1.0

Calibration Curves for Clinical Prediction Models

pmclust — 0.2-1

Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

PMCMR — 4.4

Calculate Pairwise Multiple Comparisons of Mean Rank Sums

PMCMRplus — 1.9.12

Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended

pmd — 0.2.1

Paired Mass Distance Analysis for GC/LC-MS Based Non-Targeted Analysis and Reactomics Analysis

pMEM — 0.1-1

Predictive Moran's Eigenvector Maps

pmetar — 0.5.0

Processing METAR Weather Reports

pmev — 0.1.2

Calculates Earned Value for a Project Schedule

PMEvapotranspiration — 0.1.0

Calculation of the Penman-Monteith Evapotranspiration using Weather Variables

pmhtutorial — 1.5

Minimal Working Examples for Particle Metropolis-Hastings

pmledecon — 0.2.1

Deconvolution Density Estimation using Penalized MLE

pmml — 2.5.2

Generate PMML for Various Models

pmmlTransformations — 1.3.3

Transforms Input Data from a PMML Perspective

pmparser — 1.0.20

Create and Maintain a Relational Database of Data from PubMed/MEDLINE

pmr — 1.2.5.1

Probability Models for Ranking Data

pmsampsize — 1.1.3

Sample Size for Development of a Prediction Model

pmultinom — 1.0.0

One-Sided Multinomial Probabilities

pmvalsampsize — 0.1.0

Sample Size for External Validation of a Prediction Model

pmwg — 0.2.7

Particle Metropolis Within Gibbs

PMwR — 1.0-1

Portfolio Management with R

pmxcode — 0.1.4

Create Pharmacometric Models

pmxcv — 0.0.1.0

Integration-Based Coefficients of Variance

pmxpartab — 0.5.0

Parameter Tables for PMx Analyses

pmxTools — 1.3

Pharmacometric and Pharmacokinetic Toolkit

PNADcIBGE — 0.7.5

Downloading, Reading and Analyzing PNADC Microdata

PNAR — 1.7

Poisson Network Autoregressive Models

PNDSIBGE — 0.1.1

Downloading, Reading and Analyzing PNDS Microdata - Package in Development

png — 0.1-8

Read and write PNG images

PNSIBGE — 0.2.1

Downloading, Reading and Analyzing PNS Microdata

PNWColors — 0.1.0

Color Palettes Inspired by Nature in the US Pacific Northwest

PoA — 1.2.1

Finds the Price of Anarchy for Routing Games

pocketapi — 0.1

Wrapper Around the 'Pocket' API

POCRE — 0.6.0

Penalized Orthogonal-Components Regression

pocrm — 0.13

Dose Finding in Drug Combination Phase I Trials Using PO-CRM

POD — 1.2.0

Probability of Detection for Qualitative PCR Methods

PoDBAY — 1.4.3

Vaccine Efficacy Estimation Package

podcleaner — 0.1.2

Legacy Scottish Post Office Directories Cleaner

PODES — 0.1.0

Village Potential Statistics of Indonesia

poems — 1.3.1

Pattern-Oriented Ensemble Modeling System

POET — 2.0

Principal Orthogonal ComplEment Thresholding (POET) Method

pogit — 1.3.0

Bayesian Variable Selection for a Poisson-Logistic Model

PogromcyDanych — 1.7.1

DataCrunchers (PogromcyDanych) is the Massive Online Open Course that Brings R and Statistics to the People

poibin — 1.6

The Poisson Binomial Distribution

PoiClaClu — 1.0.2.1

Classification and Clustering of Sequencing Data Based on a Poisson Model

poilog — 0.4.2.1

Poisson Lognormal and Bivariate Poisson Lognormal Distribution

POINT — 1.3

Protein Structure Guided Local Test

pointblank — 0.12.2

Data Validation and Organization of Metadata for Local and Remote Tables

pointdensityP — 0.3.5

Point Density for Geospatial Data

PointedSDMs — 2.1.2

Fit Models Derived from Point Processes to Species Distributions using 'inlabru'

PointFore — 0.2.0

Interpretation of Point Forecasts as State-Dependent Quantiles and Expectiles

pointr — 0.2.0

Working Comfortably with Pointers and Shortcuts to R Objects

pointRes — 2.0.2

Analyzing Pointer Years and Components of Resilience

PoisBinNonNor — 1.3.3

Data Generation with Poisson, Binary and Continuous Components

poisbinom — 1.0.1

A Faster Implementation of the Poisson-Binomial Distribution

PoisBinOrd — 1.4.3

Data Generation with Poisson, Binary and Ordinal Components

PoisBinOrdNonNor — 1.5.3

Generation of Up to Four Different Types of Variables

PoisBinOrdNor — 1.6.3

Data Generation with Poisson, Binary, Ordinal and Normal Components

poisDoubleSamp — 1.1.1

Confidence Intervals with Poisson Double Sampling

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