All packages

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graphPAF — 2.0.0

Estimating and Displaying Population Attributable Fractions

graphql — 1.5.1

A GraphQL Query Parser

graphsim — 1.0.3

Simulate Expression Data from 'igraph' Networks

graphTweets — 0.5.3

Visualise Twitter Interactions

graposas — 1.0.0

Graphical Approach Optimal Sample Size

grateful — 0.2.10

Facilitate Citation of R Packages

grates — 1.2.2

Grouped Date Classes

gratia — 0.9.2

Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'

graticule — 0.4.0

Meridional and Parallel Lines for Maps

gratis — 1.0.7

Generating Time Series with Diverse and Controllable Characteristics

grattan — 2024.1.1

Australian Tax Policy Analysis

grattanInflators — 0.5.4

Inflators for Australian Policy Analysis

gRaven — 1.1.8

Bayes Nets: 'RHugin' Emulation with 'gRain'

gravitas — 0.1.3

Explore Probability Distributions for Bivariate Temporal Granularities

gravity — 1.1

Estimation Methods for Gravity Models

gravmagsubs — 1.0.1

Gravitational and Magnetic Attraction of 3-D Vertical Rectangular Prisms

gRbase — 2.0.2

A Package for Graphical Modelling in R

gRc — 0.5.0

Inference in Graphical Gaussian Models with Edge and Vertex Symmetries

GRCdata — 1.0

Parameter Inference and Optimal Designs for Grouped and/or Right-Censored Count Data

GRCdesigns — 1.0.0

Generalized Row-Column Designs

GRCRegression — 1.0

Modified Poisson Regression of Grouped and Right-Censored Counts

greatR — 2.0.0

Gene Registration from Expression and Time-Courses in R

grec — 1.6.0

Gradient-Based Recognition of Spatial Patterns in Environmental Data

greed — 0.6.1

Clustering and Model Selection with the Integrated Classification Likelihood

GreedyEPL — 1.2

Greedy Expected Posterior Loss

GreedyExperimentalDesign — 1.5.6.1

Greedy Experimental Design Construction

GreedyExperimentalDesignJARs — 1.0

GreedyExperimentalDesign JARs

greekLetters — 1.0.2

Routines for Writing Greek Letters and Mathematical Symbols on the 'RStudio' and 'RGui'

greeks — 1.4.3

Sensitivities of Prices of Financial Options and Implied Volatilities

greenclust — 1.1.1

Combine Categories Using Greenacre's Method

greencrab.toolkit — 0.2

Run 'Stan' Models to Interpret Green Crab Monitoring Assessments

GREENeR — 1.0.0

Geospatial Regression Equation for European Nutrient Losses (GREEN)

Greg — 2.0.2

Regression Helper Functions

GregoryQuadrature — 1.0.0

Gregory Weights for Function Integration

gregRy — 0.1.0

GREGORY Estimation

GRelevance — 1.0

Graph-Based k-Sample Comparisons and Relevance Analysis in High Dimensions

gremlin — 1.0.1

Mixed-Effects REML Incorporating Generalized Inverses

GREMLINS — 0.2.1

Generalized Multipartite Networks

greport — 0.7-4

Graphical Reporting for Clinical Trials

greta — 0.4.5

Simple and Scalable Statistical Modelling in R

greta.dynamics — 0.2.0

Modelling Structured Dynamical Systems in 'greta'

greta.gp — 0.2.1

Gaussian Process Modelling in 'greta'

gretel — 0.0.1

Generalized Path Analysis for Social Networks

gretlR — 0.1.4

A Seamless Integration of 'Gretl' and 'R'

grex — 1.9

Gene ID Mapping for Genotype-Tissue Expression (GTEx) Data

greybox — 2.0.2

Toolbox for Model Building and Forecasting

GreyModel — 0.1.0

Fitting and Forecasting of Grey Model

Greymodels — 2.0.1

Shiny App for Grey Forecasting Model

GreyZones — 0.0.5

Detection of Grey Zones in Two-Way Inter-Rater Agreement Tables

grf — 2.3.2

Generalized Random Forests

GrFA — 0.2

Group Factor Analysis

gridBase — 0.4-7

Integration of base and grid graphics

gridBezier — 1.1-1

Bezier Curves in 'grid'

GRIDCOPULA — 1.0.1

Bivariate Copula Functions Based on Regular Grid

gridDebug — 0.5-1

Debugging 'grid' Graphics

gridExtra — 2.3

Miscellaneous Functions for "Grid" Graphics

gridGeometry — 0.4-0

Polygon Geometry in 'grid'

gridGraphics — 0.5-1

Redraw Base Graphics Using 'grid' Graphics

gridGraphviz — 0.3-1

Drawing Graphs with 'grid'

GridOnClusters — 0.1.0.1

Cluster-Preserving Multivariate Joint Grid Discretization

gridOT — 1.0.1

Approximate Optimal Transport Between Two-Dimensional Grids

gridpattern — 1.2.2

'grid' Pattern Grobs

gridsampler — 0.6

A Simulation Tool to Determine the Required Sample Size for Repertory Grid Studies

gridstackeR — 0.1.0

Wrapper for 'gridstack.js'

gridSVG — 1.7-5

Export 'grid' Graphics as SVG

gridtext — 0.1.5

Improved Text Rendering Support for 'Grid' Graphics

gRim — 0.3.3

Graphical Interaction Models

grImport — 0.9-7

Importing Vector Graphics

grImport2 — 0.3-3

Importing 'SVG' Graphics

GrimR — 0.5

Calculate Optical Parameters from Spindle Stage Measurements

gripp — 0.2.20

General Inverse Problem Platform

grizbayr — 1.3.5

Bayesian Inference for A|B and Bandit Marketing Tests

grmsem — 1.1.0

Genetic-Relationship-Matrix Structural Equation Modelling (GRMSEM)

grnn — 0.1.0

General regression neural network

GRNNs — 0.1.0

General Regression Neural Networks Package

GROAN — 1.3.1

Genomic Regression Workbench

grobblR — 0.2.1

Creating Flexible, Reproducible 'PDF' Reports

groc — 1.0.9

Generalized Regression on Orthogonal Components

gromovlab — 0.8-3

Gromov-Hausdorff Type Distances for Labeled Metric Spaces

groqR — 0.0.1

A Coding Assistant using the Fast AI Inference 'Groq'

groundhog — 3.2.0

Version-Control for CRAN, GitHub, and GitLab Packages

GroupBN — 1.2.0

Inferring Group Bayesian Networks using Hierarchical Feature Clustering

GroupComparisons — 0.1.0

Paired/Unpaired Parametric/Non-Parametric Group Comparisons

groupdata2 — 2.0.3

Creating Groups from Data

groupedSurv — 1.0.5.1

Efficient Estimation of Grouped Survival Models Using the Exact Likelihood Function

Grouphmap — 1.0.0

'Grouphmap' is an Automated One-Step Common Analysis of Batch Expression Profile

groupICA — 0.1.1

Independent Component Analysis for Grouped Data

groupr — 0.1.2

Groups with Inapplicable Values

grouprar — 0.1.0

Group Response Adaptive Randomization for Clinical Trials

GroupSeq — 1.4.3

Group Sequential Design Probabilities - With Graphical User Interface

GroupTest — 1.0.1

Multiple Testing Procedure for Grouped Hypotheses

groupTesting — 1.3.0

Simulating and Modeling Group (Pooled) Testing Data

groupwalk — 0.1.2

Implement the Group Walk Algorithm

groupWQS — 0.0.3

Grouped Weighted Quantile Sum Regression

grove — 1.1.1

Wavelet Functional ANOVA Through Markov Groves

growfunctions — 0.16

Bayesian Non-Parametric Dependent Models for Time-Indexed Functional Data

growR — 1.3.0

Implementation of the Vegetation Model ModVege

growth — 1.1.1

Multivariate Normal and Elliptically-Contoured Repeated Measurements Models

growthcleanr — 2.2.0

Data Cleaner for Anthropometric Measurements

growthcurver — 0.3.1

Simple Metrics to Summarize Growth Curves

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