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{
"name": "R-ExtremeBounds",
"description": "Extreme Bounds Analysis (EBA)"
},
{
"name": "R-extremefit",
"description": "Estimation of extreme conditional quantiles and probabilities"
},
{
"name": "R-extRemes",
"description": "Extreme value analysis"
},
{
"name": "R-eyelinker",
"description": "Import ASC files from EyeLink eye-trackers"
},
{
"name": "R-eyelinkReader",
"description": "Import gaze data for EyeLink eye tracker"
},
{
"name": "R-eyetrackingR",
"description": "Eye-tracking data analysis"
},
{
"name": "R-ezglm",
"description": "Selects significant non-additive interaction between two variables using fast GLM implementation"
},
{
"name": "R-ezplot",
"description": "Functions for common chart types"
},
{
"name": "R-fable",
"description": "Forecasting models for tidy time series"
},
{
"name": "R-fable.prophet",
"description": "Prophet modelling interface for fable"
},
{
"name": "R-fabletools",
"description": "Core tools for packages in the fable framework"
},
{
"name": "R-fabMix",
"description": "Overfitting Bayesian mixtures of factor analyzers with parsimonious covariance"
},
{
"name": "R-fabricatr",
"description": "Imagine your data before you collect it"
},
{
"name": "R-facmodCS",
"description": "Cross-section factor models"
},
{
"name": "R-factoextra",
"description": "Extract and visualize the results of multivariate data analyses"
},
{
"name": "R-FactoInvestigate",
"description": "Automatic description of factorial analysis"
},
{
"name": "R-FactoMineR",
"description": "Multivariate exploratory data analysis and data mining"
},
{
"name": "R-factor256",
"description": "Use raw vectors to minimize memory consumption of factors"
},
{
"name": "R-factorstochvol",
"description": "Bayesian estimation of (sparse) latent factor stochastic volatility models"
},
{
"name": "R-Factoshiny",
"description": "Perform factorial analysis from R-FactoMineR with an R-shiny application"
},
{
"name": "R-FAdist",
"description": "Probability distributions that are sometimes useful in hydrology"
},
{
"name": "R-fairml",
"description": "Fair models in machine learning"
},
{
"name": "R-fake",
"description": "Flexible data simulation using the multivariate normal distribution"
},
{
"name": "R-FAmle",
"description": "Maximum likelihood and Bayesian estimation of univariate probability distributions"
},
{
"name": "R-fANCOVA",
"description": "Non-parametric analysis of covariance"
},
{
"name": "R-fanovaGraph",
"description": "Kriging models from FANOVA graphs"
},
{
"name": "R-fansi",
"description": "ANSI control sequence-aware string functions"
},
{
"name": "R-far",
"description": "Modelization for functional auto-regressive processes"
},
{
"name": "R-faraway",
"description": "Functions and datasets for books by Julian Faraway"
},
{
"name": "R-farver",
"description": "High-performance color space manipulation"
},
{
"name": "R-fasta",
"description": "Fast Adaptive Shrinkage/Thresholding Algorithm"
},
{
"name": "R-fastadi",
"description": "Self-tuning data-adaptive matrix imputation"
},
{
"name": "R-fastAFT",
"description": "Fast regression for the accelerated failure time (AFT) model"
},
{
"name": "R-fastcluster",
"description": "Fast hierarchical clustering routines for R"
},
{
"name": "R-fastcmh",
"description": "Significant interval discovery with categorical covariates"
},
{
"name": "R-fastcpd",
"description": "Fast change point detection via sequential gradient descent"
},
{
"name": "R-fastDummies",
"description": "Fast creation of dummy (binary) columns and rows from categorical variables"
},
{
"name": "R-fasterize",
"description": "Fast polygon to raster conversion"
},
{
"name": "R-FastGaSP",
"description": "Fast and exact computation of Gaussian stochastic process"
},
{
"name": "R-fastGHQuad",
"description": "Fast Rcpp implementation of Gauss–Hermite quadrature"
},
{
"name": "R-fastglm",
"description": "Fast and stable fitting of generalized linear models using RcppEigen"
},
{
"name": "R-FastGP",
"description": "Efficiently use Gaussian processes with R-Rcpp and R-RcppEigen"
},
{
"name": "R-fastICA",
"description": "FastICA algorithms to perform ICA and projection pursuit"
},
{
"name": "R-FastImputation",
"description": "Learn from training data, then quickly fill in missing data"
},
{
"name": "R-FastJM",
"description": "Semi-parametric joint modeling of longitudinal and survival data"
},
{
"name": "R-fastkqr",
"description": "Fast Algorithm for Kernel Quantile Regression"
},
{
"name": "R-fastmap",
"description": "Fast map implementation for R"
},
{
"name": "R-fastmatch",
"description": "Fast match() function"
},
{
"name": "R-fastMatMR",
"description": "High-performance matrix market file operations"
},
{
"name": "R-fastmatrix",
"description": "Fast computation of some matrices useful in statistics"
}
]
}