All packages

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SpecDetec — 1.0.0

Change Points Detection with Spectral Clustering

SpecHelpers — 0.2.7

Spectroscopy Related Utilities

SPECIES — 1.1.4

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

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

spectralGraphTopology — 0.2.3

Learning Graphs from Data via Spectral Constraints

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

Spectrum — 1.1

Fast Adaptive Spectral Clustering for Single and Multi-View Data

sped — 0.3

Multi-Gene Descent Probabilities

spedecon — 0.1

Smoothness-Penalized Deconvolution for Density Estimation Under Measurement Error

SPEDInstabR — 2.2

Estimation of the Relative Importance of Factors Affecting Species Distribution Based on Stability Concept

speech — 0.1.5

Legislative Speeches

speechbr — 2.0.0

Access the Speechs and Speaker's Informations of House of Representatives of Brazil

speedglm — 0.3-5

Fitting Linear and Generalized Linear Models to Large Data Sets

speedycode — 0.3.0

Automate Code for Adding Labels, Recoding and Renaming Variables, and Converting ASCII Files

speedytax — 1.0.4

Rapidly Import Classifier Results into 'phyloseq'

spef — 1.0.9

Semiparametric Estimating Functions

speff2trial — 1.0.5

Semiparametric Efficient Estimation for a Two-Sample Treatment Effect

SPEI — 1.8.1

Calculation of the Standardized Precipitation-Evapotranspiration Index

spellcheckr — 0.1.2

Correct the Spelling of a Given Word in the English Language

spelling — 2.3.0

Tools for Spell Checking in R

spemd — 0.1-1

A Bi-Dimensional Implementation of the Empirical Mode Decomposition for Spatial Data

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

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