All packages

· A · B · C · D · E · F · G · H · I · J · K · L · M · N · O · P · Q · R · S · T · U · V · W · X · Y · Z ·

pedbuildr — 0.3.0

Pedigree Reconstruction

pedFamilias — 0.2.4

Import and Export 'Familias' Files

pedgene — 3.9

Gene-Level Variant Association Tests for Pedigree Data

pedigree — 1.4.2

Pedigree Functions

pedigreemm — 0.3-4

Pedigree-Based Mixed-Effects Models

pedigreeTools — 0.2

Versatile Functions for Working with Pedigrees

pedMermaid — 1.0.2

Pedigree Mermaid Syntax

pedmut — 0.7.1

Mutation Models for Pedigree Likelihood Computations

pedometrics — 0.12.1

Miscellaneous Pedometric Tools

pedprobr — 0.9.4

Probability Computations on Pedigrees

pedquant — 0.2.4

Public Economic Data and Quantitative Analysis

pedSimulate — 1.4.3

Pedigree, Genetic Merit, Phenotype, and Genotype Simulation

pedsuite — 1.3.1

Easy Installation of the 'pedsuite' Packages for Pedigree Analysis

pedtools — 2.7.1

Creating and Working with Pedigrees and Marker Data

pedtricks — 0.4.2

Visualize, Summarize and Simulate Data from Pedigrees

peermodels — 0.10.3

Client-Side R API Wrapper for Peer Models Network Model Repository

PeerPerformance — 2.2.5

Luck-Corrected Peer Performance Analysis in R

pegas — 1.3

Population and Evolutionary Genetics Analysis System

PEGroupTesting — 1.0

Population Proportion Estimation using Group Testing

PEIMAN2 — 0.1.0

Post-Translational Modification Enrichment, Integration, and Matching Analysis

PEIP — 2.2-5

Geophysical Inverse Theory and Optimization

PEkit — 1.0.0.1000

Partition Exchangeability Toolkit

pell — 0.1.0

Data About Historic Pell Grant Distribution in the US

PELVIS — 2.0.4

Probabilistic Sex Estimate using Logistic Regression, Based on VISual Traits of the Human Os Coxae

pema — 0.1.3

Penalized Meta-Analysis

pempi — 1.0.0

Proportion Estimation with Marginal Proxy Information

pems.utils — 0.2.29.1

Portable Emissions (and Other Mobile) Measurement System Utilities

pemultinom — 0.1.0

L1-Penalized Multinomial Regression with Statistical Inference

penAFT — 0.3.0

Fit the Regularized Gehan Estimator with Elastic Net and Sparse Group Lasso Penalties

penalized — 0.9-52

L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation in GLMs and in the Cox Model

penalizedcdf — 0.1.0

Estimate a Penalized Linear Model using the CDF Penalty Function

penalizedclr — 2.0.0

Integrative Penalized Conditional Logistic Regression

penalizedSVM — 1.1.4

Feature Selection SVM using Penalty Functions

penaltyLearning — 2024.9.3

Penalty Learning

pencal — 2.2.2

Penalized Regression Calibration (PRC) for the Dynamic Prediction of Survival

pencopulaCond — 0.2

Estimating Non-Simplified Vine Copulas Using Penalized Splines

PenCoxFrail — 2.0.0

Regularization in Cox Frailty Models

pendensity — 0.2.13

Density Estimation with a Penalized Mixture Approach

penfa — 0.1.1

Single- And Multiple-Group Penalized Factor Analysis

PenIC — 1.0.0

Semiparametric Regression Analysis of Interval-Censored Data using Penalized Splines

penMSM — 0.99

Estimating Regularized Multi-state Models Using L1 Penalties

penPHcure — 1.0.2

Variable Selection in PH Cure Model with Time-Varying Covariates

penppml — 0.2.3

Penalized Poisson Pseudo Maximum Likelihood Regression

pense — 2.2.2

Penalized Elastic Net S/MM-Estimator of Regression

pensim — 1.3.6

Simulation of High-Dimensional Data and Parallelized Repeated Penalized Regression

pensynth — 0.5.1

Penalized Synthetic Control Estimation

peopleanalytics — 0.1.0

Data Sets for Craig Starbuck's Book, "The Fundamentals of People Analytics: With Applications in R"

peopleanalyticsdata — 0.2.1

Data Sets for Keith McNulty's Handbook of Regression Modeling in People Analytics

pEPA — 1.0

Tests of Equal Predictive Accuracy for Panels of Forecasts

PEPBVS — 1.0

Bayesian Variable Selection using Power-Expected-Posterior Prior

pepe — 1.2.0

Data Manipulation

peperr — 1.5

Parallelised Estimation of Prediction Error

peppm — 0.0.1

Piecewise Exponential Distribution with Random Time Grids

pepr — 0.5.0

Reading Portable Encapsulated Projects

PepSAVIms — 0.9.1

PepSAVI-MS Data Analysis

Peptides — 2.4.6

Calculate Indices and Theoretical Physicochemical Properties of Protein Sequences

peptoolkit — 0.0.1

A Toolkit for Using Peptide Sequences in Machine Learning

peramo — 0.1.3

Permutation Tests for Randomization Model

perARMA — 1.7

Periodic Time Series Analysis

Perc — 0.1.6

Using Percolation and Conductance to Find Information Flow Certainty in a Direct Network

perccalc — 1.0.5

Estimate Percentiles from an Ordered Categorical Variable

PerFit — 1.4.6

Person Fit

PerfMeas — 1.2.5

Performance Measures for Ranking and Classification Tasks

performance — 0.12.3

Assessment of Regression Models Performance

PerformanceAnalytics — 2.0.4

Econometric Tools for Performance and Risk Analysis

performanceEstimation — 1.1.0

An Infra-Structure for Performance Estimation of Predictive Models

peRiodiCS — 0.5.0

Functions for Generating Periodic Curves

PeriodicTable — 0.1.2

Periodic Table of the Elements

periscope — 1.0.4

Enterprise Streamlined 'Shiny' Application Framework

periscope2 — 0.2.3

Enterprise Streamlined 'shiny' Application Framework Using 'bs4Dash'

PERK — 0.0.9.2

Predicting Environmental Concentration and Risk

perm — 1.0-0.4

Exact or Asymptotic Permutation Tests

PermAlgo — 1.2

Permutational Algorithm to Simulate Survival Data

PERMANOVA — 0.2.0

Multivariate Analysis of Variance Based on Distances and Permutations

PerMat — 0.1.0

Performance Metrics in Predictive Modeling

permChacko — 1.0.1

Chacko Test for Order-Restriction with Permutation

PermCor — 0.1.0

Robust Permutation Tests of Correlation Coefficients

permGS — 0.2.5

Permutational Group Sequential Test for Time-to-Event Data

permimp — 1.0-2

Conditional Permutation Importance

permPATH — 1.3

Permutation Based Gene Expression Pathway Analysis

perms — 1.14

Fast Permutation Computation

permubiome — 1.3.2

A Permutation Based Test for Biomarker Discovery in Microbiome Data

permuco — 1.1.3

Permutation Tests for Regression, (Repeated Measures) ANOVA/ANCOVA and Comparison of Signals

PermutationR — 0.1.0

Conduct Permutation Analysis of Variance in R

permutations — 1.1-5

The Symmetric Group: Permutations of a Finite Set

permute — 0.9-7

Functions for Generating Restricted Permutations of Data

permutes — 2.8

Permutation Tests for Time Series Data

permutest — 1.0.0

Run Permutation Tests and Construct Associated Confidence Intervals

perplexR — 0.0.3

A Coding Assistant using Perplexity's Large Language Models

perry — 0.3.1

Resampling-Based Prediction Error Estimation for Regression Models

perryExamples — 0.1.1

Examples for Integrating Prediction Error Estimation into Regression Models

persDx — 0.5.0

Personalized Diagnostics Rules for Subgroup Identification and Personalized Biomarker Discovery

PerseusR — 0.3.4

Perseus R Interop

PersianStemmer — 1.0

Persian Stemmer for Text Analysis

PersomicsArray — 1.0

Automated Persomics Array Image Extraction

personalized — 0.2.7

Estimation and Validation Methods for Subgroup Identification and Personalized Medicine

personalized2part — 0.0.1

Two-Part Estimation of Treatment Rules for Semi-Continuous Data

personalr — 1.0.3

Automated Personal Package Setup

personr — 1.0.0

Test Your Personality

perspectev — 1.1

Permutation of Species During Turnover Events

Next page