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 ·

sperich — 1.5-9

Auxiliary Functions to Estimate Centers of Biodiversity

sperrorest — 3.0.5

Perform Spatial Error Estimation and Variable Importance Assessment

SpeTestNP — 1.1.0

Non-Parametric Tests of Parametric Specifications

SPEV — 1.0.0

Unsmoothed and Smoothed Penalized PCA using Nesterov Smoothing

spex — 0.7.1

Spatial Extent Tools

spfa — 1.0

Semi-Parametric Factor Analysis

spfda — 0.9.1

Function-on-Scalar Regression with Group-Bridge Penalty

spfilteR — 1.1.5

Semiparametric Spatial Filtering with Eigenvectors in (Generalized) Linear Models

spFSR — 2.0.4

Feature Selection and Ranking via Simultaneous Perturbation Stochastic Approximation

spFW — 0.1.0

Hierarchical Spatial Finlay-Wilkinson Model

spGARCH — 0.2.2

Spatial ARCH and GARCH Models (spGARCH)

spgs — 1.0-4

Statistical Patterns in Genomic Sequences

spgwr — 0.6-37

Geographically Weighted Regression

SphereOptimize — 0.1.1

Optimization on a Unit Sphere

spherepc — 0.1.7

Spherical Principal Curves

sphereplot — 1.5.1

Spherical Plotting

spheresmooth — 0.1.0

Piecewise Geodesic Smoothing for Spherical Data

sphereTessellation — 1.2.0

Delaunay and Voronoï Tessellations on the Sphere

SphericalCubature — 1.5

Numerical Integration over Spheres and Balls in n-Dimensions; Multivariate Polar Coordinates

sphet — 2.0

Estimation of Spatial Autoregressive Models with and without Heteroskedastic Innovations

sphunif — 1.4.0

Uniformity Tests on the Circle, Sphere, and Hypersphere

SpiceFP — 0.1.2

Sparse Method to Identify Joint Effects of Functional Predictors

spider — 1.5.0

Species Identity and Evolution in R

spiderbar — 0.2.5

Parse and Test Robots Exclusion Protocol Files and Rules

spidR — 1.0.2

Spider Knowledge Online

SPIGA — 1.0.0

Compute SPI Index using the Methods Genetic Algorithm and Maximum Likelihood

spikes — 1.1

Detecting Election Fraud from Irregularities in Vote-Share Distributions

spikeslab — 1.1.6

Prediction and Variable Selection Using Spike and Slab Regression

spikeSlabGAM — 1.1-19

Bayesian Variable Selection and Model Choice for Generalized Additive Mixed Models

Spillover — 0.1.1

Spillover/Connectedness Index Based on VAR Modelling

SPINA — 4.1.0

Structure Parameter Inference Approach

spINAR — 0.2.0

(Semi)Parametric Estimation and Bootstrapping of INAR Models

spinBayes — 0.2.1

Semi-Parametric Gene-Environment Interaction via Bayesian Variable Selection

spind — 2.2.1

Spatial Methods and Indices

spinifex — 0.3.7.0

Manual Tours, Manual Control of Dynamic Projections of Numeric Multivariate Data

spinner — 1.1.0

An Implementation of Graph Net Architecture Based on 'torch'

spinyReg — 0.1-0

Sparse Generative Model and Its EM Algorithm

spiralize — 1.1.0

Visualize Data on Spirals

spiritR — 0.1.1

Template for Clinical Trial Protocol

spiro — 0.2.1

Manage Data from Cardiopulmonary Exercise Testing

splancs — 2.01-45

Spatial and Space-Time Point Pattern Analysis

splash — 1.0.2

Simple Process-Led Algorithms for Simulating Habitats

spldv — 0.1.3

Spatial Models for Limited Dependent Variables

SPLICE — 1.1.2

Synthetic Paid Loss and Incurred Cost Experience (SPLICE) Simulator

splines2 — 0.5.3

Regression Spline Functions and Classes

splinetree — 0.2.0

Longitudinal Regression Trees and Forests

Splinets — 1.5.0

Functional Data Analysis using Splines and Orthogonal Spline Bases

SPlit — 1.2

Split a Dataset for Training and Testing

splitfngr — 0.1.2

Combined Evaluation and Split Access of Functions

SplitGLM — 1.0.5

Split Generalized Linear Models

splithalf — 0.8.2

Calculate Task Split Half Reliability Estimates

splithalfr — 2.2.2

Estimate Split-Half Reliabilities

SplitKnockoff — 1.2

Split Knockoffs for Structural Sparsity

SplitReg — 1.0.2

Split Regularized Regression

splitSelect — 1.0.3

Best Split Selection Modeling for Low-Dimensional Data

SplitSoftening — 2.1-0

Softening Splits in Decision Trees

SplitSplitPlot — 0.0.1

Analysis of Split-Split-Plot Experiments (Analise De Experimentos Em Parcela Subsubdividida)

splitstackshape — 1.4.8

Stack and Reshape Datasets After Splitting Concatenated Values

splitTools — 1.0.1

Tools for Data Splitting

splm — 1.6-5

Econometric Models for Spatial Panel Data

splmm — 1.2.0

Simultaneous Penalized Linear Mixed Effects Models

splot — 0.5.4

Simplified Plotting for Data Exploration

spls — 2.2-3

Sparse Partial Least Squares (SPLS) Regression and Classification

splus2R — 1.3-5

Supplemental S-PLUS Functionality in R

splusTimeDate — 2.5.8

Times and Dates from 'S-PLUS'

splusTimeSeries — 1.5.7

Time Series from 'S-PLUS'

splutil — 2022.6.20

Utility Functions for Common Base-R Problems Relating to Lists

spm — 1.2.2

Spatial Predictive Modeling

spm2 — 1.1.3

Spatial Predictive Modeling

spMaps — 0.5.0

Europe SpatialPolygonsDataFrame Builder

spMC — 0.3.15

Continuous-Lag Spatial Markov Chains

SPmlficmcm — 1.4

Semiparametric Maximum Likelihood Method for Interactions Gene-Environment in Case-Mother Control-Mother Designs

spmodel — 0.8.0

Spatial Statistical Modeling and Prediction

spmoran — 0.3.0

Fast Spatial and Spatio-Temporal Regression using Moran Eigenvectors

spnaf — 1.1.0

Spatial Network Autocorrelation for Flow Data

spNetwork — 0.4.4.3

Spatial Analysis on Network

SpNMF — 0.1.1

Supervised NMF

spnn — 1.2.1

Scale Invariant Probabilistic Neural Networks

spNNGP — 1.0.1

Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes

spocc — 1.2.3

Interface to Species Occurrence Data Sources

spOccupancy — 0.7.6

Single-Species, Multi-Species, and Integrated Spatial Occupancy Models

spoiler — 1.0.0

Blur 'HTML' Elements in 'Shiny' Applications Using 'Spoiler-Alert.js'

spongebob — 0.4.0

SpongeBob-Case Converter : spOngEboB-CASe CoNVertER

spongecake — 0.1.2

Transform a Movie into a Synthetic Picture

spooky — 1.4.0

Time Feature Extrapolation Using Spectral Analysis and Jack-Knife Resampling

spork — 0.3.3

Generalized Label Formatting

sport — 0.2.1

Sequential Pairwise Online Rating Techniques

SPORTSCausal — 1.0

Spillover Time Series Causal Inference

SportsTour — 0.1.0

Display Tournament Fixtures using Knock Out and Round Robin Techniques

sportyR — 2.2.2

Plot Scaled 'ggplot' Representations of Sports Playing Surfaces

spotidy — 0.1.0

Providing Convenience Functions to Connect R with the Spotify API

spotoroo — 0.1.4

Spatiotemporal Clustering of Satellite Hot Spot Data

SPOUSE — 0.1.0

Scatter Plots Over-Viewed Using Summary Ellipses

SPPcomb — 0.1

Combining Different Spatial Datasets in Cancer Risk Estimation

SpPOP — 0.1.0

Generation of Spatial Population under Different Levels of Relationships among Variables

spray — 1.0-26

Sparse Arrays and Multivariate Polynomials

spreadr — 0.2.0

Simulating Spreading Activation in a Network

SPREDA — 1.1

Statistical Package for Reliability Data Analysis

SPreg — 1.0

Bias Reduction in the Skew-Probit Model for a Binary Response

spreval — 1.1.0

Evaluation of Sprinkler Irrigation Uniformity and Efficiency

Next page