All packages

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SpatialML — 0.1.7

Spatial Machine Learning

SpatialNP — 1.1-6

Multivariate Nonparametric Methods Based on Spatial Signs and Ranks

SpatialPack — 0.4-1

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 — 1.3-6

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

spatialsample — 0.6.0

Spatial Resampling Infrastructure

spatialTIME — 1.3.4-5

Spatial Analysis of Vectra Immunoflourescent Data

SpatialTools — 1.0.5

Tools for Spatial Data Analysis

SpatialVS — 1.1

Spatial Variable Selection

SpatialVx — 1.0-3

Spatial Forecast Verification

spatialwarnings — 3.1.0

Spatial Early Warning Signals of Ecosystem Degradation

spatialwidget — 0.2.5

Formats Spatial Data for Use in Htmlwidgets

SpatMCA — 1.0.4

Regularized Spatial Maximum Covariance Analysis

SpaTopic — 1.2.0

Topic Inference to Identify Tissue Architecture in Multiplexed Images

SpatPCA — 1.3.5

Regularized Principal Component Analysis for Spatial Data

spatPomp — 1.0.0

Inference for Spatiotemporal Partially Observed Markov Processes

SpATS — 1.0-19

Spatial Analysis of Field Trials with Splines

spatsoc — 0.2.2

Group Animal Relocation Data by Spatial and Temporal Relationship

spatstat — 3.3-2

Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests

spatstat.data — 3.1-6

Datasets for 'spatstat' Family

spatstat.explore — 3.4-2

Exploratory Data Analysis for the 'spatstat' Family

spatstat.geom — 3.3-6

Geometrical Functionality of the 'spatstat' Family

spatstat.gui — 3.1-0

Interactive Graphics Functions for the 'spatstat' Package

spatstat.Knet — 3.1-2

Extension to 'spatstat' for Large Datasets on a Linear Network

spatstat.linnet — 3.2-5

Linear Networks Functionality of the 'spatstat' Family

spatstat.local — 5.1-0

Extension to 'spatstat' for Local Composite Likelihood

spatstat.model — 3.3-5

Parametric Statistical Modelling and Inference for the 'spatstat' Family

spatstat.random — 3.3-3

Random Generation Functionality for the 'spatstat' Family

spatstat.sparse — 3.1-0

Sparse Three-Dimensional Arrays and Linear Algebra Utilities

spatstat.univar — 3.1-2

One-Dimensional Probability Distribution Support for the 'spatstat' Family

spatstat.utils — 3.1-3

Utility Functions for 'spatstat'

spatsurv — 2.0-1

Bayesian Spatial Survival Analysis with Parametric Proportional Hazards Models

SPB — 1.0

Simple Progress Bars for Procedural Coding

spbabel — 0.6.0

Convert Spatial Data Using Tidy Tables

spbal — 1.0.1

Spatially Balanced Sampling Algorithms

spBayes — 0.4-8

Univariate and Multivariate Spatial-Temporal Modeling

spBayesSurv — 1.1.8

Bayesian Modeling and Analysis of Spatially Correlated Survival Data

spBFA — 1.3

Spatial Bayesian Factor Analysis

spBPS — 0.0-4

Bayesian Predictive Stacking for Scalable Geospatial Transfer Learning

Spbsampling — 1.3.5

Spatially Balanced Sampling

spc — 0.7.1

Statistical Process Control -- Calculation of ARL and Other Control Chart Performance Measures

spc4sts — 0.6.3

Statistical Process Control for Stochastic Textured Surfaces

spcadjust — 1.1

Functions for Calibrating Control Charts

SPCALDA — 1.0

A New Reduced-Rank Linear Discriminant Analysis Method

SPCAvRP — 0.4

Sparse Principal Component Analysis via Random Projections (SPCAvRP)

SPCDAnalyze — 0.1.0

Design and Analyze Studies using the Sequential Parallel Comparison Design

SPCompute — 1.0.3

Compute Power or Sample Size for GWAS with Covariate Effect

spconf — 1.0.1

Computing Scales of Spatial Smoothing for Confounding Adjustment

spcosa — 0.4-2

Spatial Coverage Sampling and Random Sampling from Compact Geographical Strata

spcov — 1.3

Sparse Estimation of a Covariance Matrix

spCP — 1.3

Spatially Varying Change Points

spcr — 2.1.1

Sparse Principal Component Regression

spd — 2.0-1

Semi Parametric Distribution

spData — 2.3.4

Datasets for Spatial Analysis

spDates — 1.1

Analysis of Spatial Gradients in Radiocarbon Dates

spdep — 1.3-11

Spatial Dependence: Weighting Schemes, Statistics

spdesign — 0.0.5

Designing Stated Preference Experiments

spdl — 0.0.5

Easier Use of 'RcppSpdlog' Functions via Wrapper

spdownscale — 0.1.0

Spatial Downscaling Using Bias Correction Approach

spduration — 0.17.2

Split-Population Duration (Cure) Regression

spdynmod — 1.1.6

Spatio-Dynamic Wetland Plant Communities Model

speakeasyR — 0.1.5

Fast and Robust Multi-Scale Graph Clustering

speakr — 3.2.4

A Wrapper for the Phonetic Software 'Praat'

speaq — 2.7.0

Tools for Nuclear Magnetic Resonance (NMR) Spectra Alignment, Peak Based Processing, Quantitative Analysis and Visualizations

spearmanCI — 1.1

Jackknife Euclidean / Empirical Likelihood Inference for Spearman's Rho

spec — 0.1.9

A Data Specification Format and Interface

speccurvieR — 0.4.2

Easy, Fast, and Pretty Specification Curve Analysis

SpecDetec — 1.0.0

Change Points Detection with Spectral Clustering

SpecHelpers — 0.3.1

Spectroscopy Related Utilities

SPECIES — 1.2.0

Statistical Package for Species Richness Estimation

specieschrom — 1.0.0

The Species Chromatogram

SPECK — 1.0.0

Receptor Abundance Estimation using Reduced Rank Reconstruction and Clustered Thresholding

specklestar — 0.0.1.7

Reduction of Speckle Data from BTA 6-m Telescope

specr — 1.0.0

Conducting and Visualizing Specification Curve Analyses

specs — 1.0.1

Single-Equation Penalized Error-Correction Selector (SPECS)

SpecsVerification — 0.5-3

Forecast Verification Routines for Ensemble Forecasts of Weather and Climate

spect — 1.0

Survival Prediction Ensemble Classification Tool

spectacles — 0.5-4

Storing, Manipulating and Analysis Spectroscopy and Associated Data

spectator — 0.2.0

Interface to the 'Spectator Earth' API

spectr — 1.0.1

Calculate the Periodogram of a Time-Course

spectral — 2.0

Common Methods of Spectral Data Analysis

spectralAnalysis — 4.3.3

Pre-Process, Visualize and Analyse Spectral Data

spectralAnomaly — 0.1.1

Detect Anomalies Using the Spectral Residual Algorithm

SpectralClMixed — 1.0.1

Spectral Clustering for Mixed Type Data

spectralGP — 1.3.3

Approximate Gaussian Processes Using the Fourier Basis

SpectralMap — 1.0

Diffusion Map and Spectral Map

spectralR — 0.1.3

Obtain and Visualize Spectral Reflectance Data for Earth Surface Polygons

Spectran — 1.0.6

Visual and Non-Visual Spectral Analysis of Light

spectre — 1.0.2

Predict Regional Community Composition

spectrino — 2.0.0

Spectra Viewer, Organizer, Data Preparation and Property Blocks

spectrolab — 0.0.19

Class and Methods for Spectral Data

Spectrum — 1.1

Fast Adaptive Spectral Clustering for Single and Multi-View Data

sped — 0.3

Multi-Gene Descent Probabilities

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