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 ·

sound — 1.4.6

A Sound Interface for R

soundClass — 0.0.9.2

Sound Classification Using Convolutional Neural Networks

soundecology — 1.3.3

Soundscape Ecology

SoundexBR — 1.2

Phonetic-Coding for Portuguese

soundgen — 2.7.0

Sound Synthesis and Acoustic Analysis

SoundShape — 1.3.0

Sound Waves Onto Morphometric Data

SoupX — 1.6.2

Single Cell mRNA Soup eXterminator

sourcetools — 0.1.7-1

Tools for Reading, Tokenizing and Parsing R Code

SouthParkRshiny — 1.0.0

Data and 'Shiny' Application for the Show 'SouthPark'

sovereign — 1.2.1

State-Dependent Empirical Analysis

sox — 1.2

Structured Learning in Time-Dependent Cox Models

SoyNAM — 1.6.2

Soybean Nested Association Mapping Dataset

SoyURT — 1.0.0

USDA Northern Region Uniform Soybean Tests Dataset

sp — 2.1-4

Classes and Methods for Spatial Data

SP2000 — 0.2.0

Catalogue of Life Toolkit

sp23design — 0.9-1

Design and Simulation of Seamless Phase II-III Clinical Trials

spaa — 0.2.2

SPecies Association Analysis

spAbundance — 0.1.3

Univariate and Multivariate Spatial Modeling of Species Abundance

spacefillr — 0.3.3

Space-Filling Random and Quasi-Random Sequences

spacejamr — 0.2.1

Simulate Spatial Bernoulli Networks

spaceNet — 1.2

Latent Space Models for Multidimensional Networks

spacesRGB — 1.5-0

Standard and User-Defined RGB Color Spaces, with Conversion Between RGB and CIE XYZ

spacesXYZ — 1.3-0

CIE XYZ and some of Its Derived Color Spaces

spacetime — 1.3-2

Classes and Methods for Spatio-Temporal Data

SpaceTimeBSS — 0.4-0

Blind Source Separation for Multivariate Spatio-Temporal Data

SpaCOAP — 1.2

High-Dimensional Spatial Covariate-Augmented Overdispersed Poisson Factor Model

spacyr — 1.3.0

Wrapper to the 'spaCy' 'NLP' Library

SPADAR — 1.0

Spherical Projections of Astronomical Data

spAddins — 0.2.0

A Set of RStudio Addins

SpadeR — 0.1.1

Species-Richness Prediction and Diversity Estimation with R

SpaDES — 2.0.11

Develop and Run Spatially Explicit Discrete Event Simulation Models

SpaDES.core — 2.1.0

Core Utilities for Developing and Running Spatially Explicit Discrete Event Models

SpaDES.tools — 2.0.7

Additional Tools for Developing Spatially Explicit Discrete Event Simulation (SpaDES) Models

spaero — 0.6.0

Software for Project AERO

spagmix — 0.4-2

Artificial Spatial and Spatio-Temporal Densities on Bounded Windows

spam — 2.10-0

SPArse Matrix

spam64 — 2.10-0

64-Bit Extension of the SPArse Matrix R Package 'spam'

spaMM — 4.5.0

Mixed-Effect Models, with or without Spatial Random Effects

spanish — 0.4.2

Translate Quantities from Strings to Integer and Back. Misc Functions on Spanish Data

spANOVA — 0.99.4

Analysis of Field Trials with Geostatistics & Spatial AR Models

spant — 2.23.0

MR Spectroscopy Analysis Tools

sparcl — 1.0.4

Perform Sparse Hierarchical Clustering and Sparse K-Means Clustering

spark.sas7bdat — 1.4

Read in 'SAS' Data ('.sas7bdat' Files) into 'Apache Spark'

sparkavro — 0.3.0

Load Avro file into 'Apache Spark'

sparkbq — 0.1.1

Google 'BigQuery' Support for 'sparklyr'

sparkhail — 0.1.1

A 'Sparklyr' Extension for 'Hail'

sparkline — 2.0

'jQuery' Sparkline 'htmlwidget'

sparklyr — 1.8.6

R Interface to Apache Spark

sparklyr.flint — 0.2.2

Sparklyr Extension for 'Flint'

sparklyr.nested — 0.0.4

A 'sparklyr' Extension for Nested Data

sparktex — 0.1

Generate LaTeX sparklines in R

sparktf — 0.1.0

Interface for 'TensorFlow' 'TFRecord' Files with 'Apache Spark'

sparkwarc — 0.1.6

Load WARC Files into Apache Spark

sparkxgb — 0.2.0

Interface for 'XGBoost' on 'Apache Spark'

sparr — 2.3-15

Spatial and Spatiotemporal Relative Risk

SPARRAfairness — 0.0.0.1

Analysis of Differential Behaviour of SPARRA Score Across Demographic Groups

sparrpowR — 0.2.8

Power Analysis to Detect Spatial Relative Risk Clusters

sparseBC — 1.2

Sparse Biclustering of Transposable Data

SparseBiplots — 4.0.1

'HJ-Biplot' using Different Ways of Penalization Plotting with 'ggplot2'

SparseChol — 0.3.1

Sparse Matrix C++ Classes Including Sparse Cholesky LDL Decomposition of Symmetric Matrices

sparseCov — 0.0.1

Sparse Covariance Estimation Based on Thresholding

SparseDC — 0.1.17

Implementation of SparseDC Algorithm

sparseDFM — 1.0

Estimate Dynamic Factor Models with Sparse Loadings

sparsediscrim — 0.3.0

Sparse and Regularized Discriminant Analysis

sparseEigen — 0.1.0

Computation of Sparse Eigenvectors of a Matrix

sparseFLMM — 0.4.1

Functional Linear Mixed Models for Irregularly or Sparsely Sampled Data

SparseFunClust — 1.0.0

Sparse Functional Clustering

sparsegl — 1.1.1

Sparse Group Lasso

SparseGrid — 0.8.2

Sparse grid integration in R

sparseHessianFD — 0.3.3.7

Numerical Estimation of Sparse Hessians

sparseIndexTracking — 0.1.1

Design of Portfolio of Stocks to Track an Index

sparseinv — 0.1.3

Computation of the Sparse Inverse Subset

sparseLDA — 0.1-9

Sparse Discriminant Analysis

SparseLPM — 1.0

The Sparse Latent Position Model for Nonnegative Interaction Data

sparseLRMatrix — 0.1.0

Represent and Use Sparse + Low Rank Matrices

sparseLTSEigen — 0.2.0.1

RcppEigen back end for sparse least trimmed squares regression

SparseM — 1.84-2

Sparse Linear Algebra

sparseMatEst — 1.0.0

Sparse Matrix Estimation and Inference

SparseMDC — 0.99.5

Implementation of SparseMDC Algorithm

SPARSEMODr — 1.2.0

SPAtial Resolution-SEnsitive Models of Outbreak Dynamics

SparseMSE — 2.0.1

'Multiple Systems Estimation for Sparse Capture Data'

sparseMVN — 0.2.2

Multivariate Normal Functions for Sparse Covariance and Precision Matrices

sparsenet — 1.6

Fit Sparse Linear Regression Models via Nonconvex Optimization

sparsepca — 0.1.2

Sparse Principal Component Analysis (SPCA)

sparsepp — 1.22

'Rcpp' Interface to 'sparsepp'

sparseR — 0.3.1

Variable Selection under Ranked Sparsity Principles for Interactions and Polynomials

sparsereg — 1.2

Sparse Bayesian Models for Regression, Subgroup Analysis, and Panel Data

sparseSEM — 4.0

Elastic Net Penalized Maximum Likelihood for Structural Equation Models with Network GPT Framework

sparsestep — 1.0.1

SparseStep Regression

sparsesvd — 0.2-2

Sparse Truncated Singular Value Decomposition (from 'SVDLIBC')

sparseSVM — 1.1-6

Solution Paths of Sparse High-Dimensional Support Vector Machine with Lasso or Elastic-Net Regularization

SparseTSCGM — 4.0

Sparse Time Series Chain Graphical Models

sparsevar — 0.1.0

Sparse VAR/VECM Models Estimation

sparsevb — 0.1.0

Spike-and-Slab Variational Bayes for Linear and Logistic Regression

sparsevctrs — 0.1.0

Sparse Vectors for Use in Data Frames

SparseVFC — 0.1.2

Sparse Vector Field Consensus for Vector Field Learning

sparsio — 1.0.1

I/O Operations with Sparse Matrices

sparta — 0.8.4

Sparse Tables

SPARTAAS — 1.2.4

Statistical Pattern Recognition and daTing using Archaeological Artefacts assemblageS

sparvaride — 0.1.0

Variance Identification in Sparse Factor Analysis

Next page