All packages

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exploratory — 0.3.31

A Tool for Large-Scale Exploratory Analyses

explore — 1.3.3

Simplifies Exploratory Data Analysis

exploreR — 0.1

Tools for Quickly Exploring Data

expm — 1.0-0

Matrix Exponential, Log, 'etc'

export — 0.3.0

Streamlined Export of Graphs and Data Tables

ExPosition — 2.8.23

Exploratory Analysis with the Singular Value Decomposition

ExposR — 1.2

Models Topographic Exposure to Hurricane Winds

expowo — 2.0

Data Mining of Plant Diversity and Distribution

expperm — 1.6

Computing Expectations and Marginal Likelihoods for Permutations

ExpRep — 1.0

Experiment Repetitions

expSBM — 1.3.5

An Exponential Stochastic Block Model for Interaction Lengths

expsmooth — 2.3

Data Sets from "Forecasting with Exponential Smoothing"

expss — 0.11.6

Tables, Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics

expstudy — 2.0.0

Tools for Actuarial Experience Studies

exreport — 0.4.1

Fast, Reliable and Elegant Reproducible Research

EXRQ — 1.0

Extreme Regression of Quantiles

extBatchMarking — 1.1.0

Extended Batch Marking Models

ExtDist — 0.7-2

Extending the Range of Functions for Probability Distributions

extendedFamily — 0.2.4

Additional Families for Generalized Linear Models

exteriorMatch — 1.0.0

Constructs the Exterior Match from Two Matched Control Groups

extlasso — 0.3

Maximum Penalized Likelihood Estimation with Extended Lasso Penalty

ExtMallows — 0.1.0

An Extended Mallows Model and Its Hierarchical Version for Ranked Data Aggregation

ExtractTrainData — 9.1.6

Extract Values from Raster

extraDistr — 1.10.0

Additional Univariate and Multivariate Distributions

extrafont — 0.19

Tools for Using Fonts

extrafontdb — 1.0

Package for holding the database for the extrafont package

extrafrail — 1.12

Estimation and Additional Tools for Alternative Shared Frailty Models

extraoperators — 0.3.0

Extra Binary Relational and Logical Operators

extras — 0.7.3

Helper Functions for Bayesian Analyses

extrasteps — 0.1.0

More Miscellaneous Steps for the 'recipes' Package

extraterrestrial — 0.1.0

Astrobiology Equations Estimating Extraterrestrial Life

extRatum — 1.0.4

Summary Statistics for Geospatial Features

extRC — 1.2

Extended RC Models for Contingency Tables

ExtremalDep — 0.0.4-2

Extremal Dependence Models

ExtremeBounds — 0.1.7

Extreme Bounds Analysis (EBA)

extremefit — 1.0.2

Estimation of Extreme Conditional Quantiles and Probabilities

extremeIndex — 0.0.3

Forecast Verification for Extreme Events

extrememix — 0.0.1

Bayesian Estimation of Extreme Value Mixture Models

ExtremeRisks — 0.0.4

Extreme Risk Measures

extRemes — 2.1-4

Extreme Value Analysis

extremeStat — 1.5.9

Extreme Value Statistics and Quantile Estimation

extremevalues — 2.3.4

Univariate Outlier Detection

extremis — 1.2.1

Statistics of Extremes

extremogram — 1.0.2

Estimation of Extreme Value Dependence for Time Series Data

ExtrPatt — 0.1-4

Spatial Dependencies and Indices for Extremes

exuber — 1.0.2

Econometric Analysis of Explosive Time Series

exvatools — 0.9.0

Value Added in Exports and Other Input-Output Table Analysis Tools

eye — 1.2.1

Analysis of Eye Data

eyedata — 0.1.0

Open Source Ophthalmic Data Sets Curated for R

eyelinker — 0.2.1

Import ASC Files from EyeLink Eye Trackers

eyelinkReader — 1.0.2

Import Gaze Data for EyeLink Eye Tracker

eyeRead — 0.0.4

Prepare/Analyse Eye Tracking Data for Reading

eyetools — 0.7.2

Analyse Eye Data

eyetrackingR — 0.2.1

Eye-Tracking Data Analysis

eyeTrackR — 1.0.1

Organising and Analysing Eye-Tracking Data

ez — 4.4-0

Easy Analysis and Visualization of Factorial Experiments

ez.combat — 1.0.0

Easy ComBat Harmonization

ezcox — 1.0.4

Easily Process a Batch of Cox Models

ezCutoffs — 1.0.1

Fit Measure Cutoffs in SEM

ezec — 1.0.1

Easy Interface to Effective Concentration Calculations

ezECM — 1.0.0

Event Categorization Matrix Classification for Nuclear Detonations

ezEDA — 0.1.1

Task Oriented Interface for Exploratory Data Analysis

EzGP — 0.1.0

Easy-to-Interpret Gaussian Process Models for Computer Experiments

ezknitr — 0.6.3

Avoid the Typical Working Directory Pain When Using 'knitr'

ezmmek — 0.2.4

Easy Michaelis-Menten Enzyme Kinetics

ezplot — 0.7.13

Functions for Common Chart Types

ezr — 0.1.5

Easy Use of R via Shiny App for Basic Analyses of Experimental Data

EZtune — 3.1.1

Tunes AdaBoost, Elastic Net, Support Vector Machines, and Gradient Boosting Machines

f1dataR — 1.6.0

Access Formula 1 Data

FaaSr — 1.3.0

FaaS (Function as a Service) Package

fabCI — 0.2

FAB Confidence Intervals

FABInference — 0.1

FAB p-Values and Confidence Intervals

fabisearch — 0.0.4.5

Change Point Detection in High-Dimensional Time Series Networks

fable — 0.4.1

Forecasting Models for Tidy Time Series

fable.ata — 0.0.6

'ATAforecasting' Modelling Interface for 'fable' Framework

fable.prophet — 0.1.0

Prophet Modelling Interface for 'fable'

fableCount — 0.1.0

INGARCH and GLARMA Models for Count Time Series in Fable Framework

fabletools — 0.5.0

Core Tools for Packages in the 'fable' Framework

fabMix — 5.1

Overfitting Bayesian Mixtures of Factor Analyzers with Parsimonious Covariance and Unknown Number of Components

fabPrediction — 1.0.4

Compute FAB (Frequentist and Bayes) Conformal Prediction Intervals

fabR — 2.1.0

Wrapper Functions Collection Used in Data Pipelines

fabricatr — 1.0.2

Imagine Your Data Before You Collect It

fabricerin — 0.1.2

Create Easily Canvas in 'shiny' and 'RMarkdown' Documents

face — 0.1-7

Fast Covariance Estimation for Sparse Functional Data

facebookadsR — 0.1.0

Access to Facebook Ads via the 'Windsor.ai' API

facebookleadsR — 0.1.0

Get Facebook Leads Ads Data via the 'Windsor.ai' API

facebookorganicR — 0.1.0

Get Data from 'Facebook Organic' via the 'Windsor.ai' API

facerec — 0.1.0

An Interface for Face Recognition

facmodCS — 1.0

Cross-Section Factor Models

facmodTS — 1.0

Time Series Factor Models for Asset Returns

FACT — 0.1.1

Feature Attributions for ClusTering

factiv — 0.1.0

Instrumental Variables Estimation for 2^k Factorial Experiments

FACTMLE — 1.1

Maximum Likelihood Factor Analysis

FactoClass — 1.2.9

Combination of Factorial Methods and Cluster Analysis

factoextra — 1.0.7

Extract and Visualize the Results of Multivariate Data Analyses

FactoInvestigate — 1.9

Automatic Description of Factorial Analysis

FactoMineR — 2.11

Multivariate Exploratory Data Analysis and Data Mining

factoptd — 1.0.3

Factorial Optimal Designs for Two-Colour cDNA Microarray Experiments

factor.switching — 1.4

Post-Processing MCMC Outputs of Bayesian Factor Analytic Models

factor256 — 0.1.0

Use Raw Vectors to Minimize Memory Consumption of Factors

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