All packages

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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 — 1.1-7

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

SPAS — 2024.1.31

Stratified-Petersen Analysis System

spass — 1.3

Study Planning and Adaptation of Sample Size

spate — 1.7.5

Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach

SpatEntropy — 2.2-4

Spatial Entropy Measures

SPAtest — 3.1.2

Score Test and Meta-Analysis Based on Saddlepoint Approximation

SpatFD — 0.0.1

Functional Geostatistics: Univariate and Multivariate Functional Spatial Prediction

SpatGC — 0.1.0

Bayesian Modeling of Spatial Count Data

spatgeom — 0.3.0

Geometric Spatial Point Analysis

spatgraphs — 3.4

Graph Edge Computations for Spatial Point Patterns

SpatGRID — 0.1.0

Spatial Grid Generation from Longitude and Latitude List

spathial — 0.1.2

Evolutionary Analysis

spaths — 1.1.3

Shortest Paths Between Points in Grids

spatial — 7.3-17

Functions for Kriging and Point Pattern Analysis

SpatialAcc — 0.1-5

Spatial Accessibility Measures

SpatialBSS — 0.14-0

Blind Source Separation for Multivariate Spatial Data

spatialCovariance — 0.6-9

Computation of Spatial Covariance Matrices for Data on Rectangles

SpatialDDLS — 1.0.2

Deconvolution of Spatial Transcriptomics Data Based on Neural Networks

spatialEco — 2.0-2

Spatial Analysis and Modelling Utilities

SpatialEpi — 1.2.8

Methods and Data for Spatial Epidemiology

SpatialExtremes — 2.1-0

Modelling Spatial Extremes

SpatialfdaR — 1.0.0

Spatial Functional Data Analysis

SpatialGEV — 1.0.1

Fit Spatial Generalized Extreme Value Models

SpatialGraph — 1.0-4

The SpatialGraph Class and Utilities

spatialising — 0.6.0

Ising Model for Spatial Data

SpatialKDE — 0.8.2

Kernel Density Estimation for Spatial Data

SpatialKWD — 0.4.1

Spatial KWD for Large Spatial Maps

SpatialML — 0.1.7

Spatial Machine Learning

SpatialNP — 1.1-5

Multivariate Nonparametric Methods Based on Spatial Signs and Ranks

SpatialPack — 0.4

Tools for Assessment the Association Between Two Spatial Processes

SpatialPOP — 0.1.0

Generation of Spatial Data with Spatially Varying Model Parameter

SpatialPosition — 2.1.2

Spatial Position Models

spatialprobit — 1.0.4

Spatial Probit Models

SpatialRDD — 0.1.0

Conduct Multiple Types of Geographic Regression Discontinuity Designs

spatialreg — 1.3-5

Spatial Regression Analysis

SpatialRegimes — 1.1

Spatial Constrained Clusterwise Regression

spatialRF — 1.1.4

Easy Spatial Modeling with Random Forest

spatialrisk — 0.7.1

Calculating Spatial Risk

SpatialRoMLE — 0.1.0

Robust Maximum Likelihood Estimation for Spatial Error Model

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