All packages

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smatr — 3.4-8

(Standardised) Major Axis Estimation and Testing Routines

smbinning — 0.9

Scoring Modeling and Optimal Binning

SmCCNet — 2.0.3

Sparse Multiple Canonical Correlation Network Analysis Tool

smcfcs — 1.9.0

Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification

SMCRM — 0.0-3

Data Sets for Statistical Methods in Customer Relationship Management by Kumar and Petersen (2012).

smcryptoR — 0.1.2

ShangMi(SM) Cryptographic Algorithms(SM2/SM3/SM4)

smcure — 2.1

Fit Semiparametric Mixture Cure Models

smd — 0.7.0

Compute Standardized Mean Differences

smdata — 1.2

Data to Accompany Smithson & Merkle, 2013

smdi — 0.3.1

Perform Structural Missing Data Investigations

SMDIC — 0.1.6

Identification of Somatic Mutation-Driven Immune Cells

smdocker — 0.1.4

Build 'Docker Images' in 'Amazon SageMaker Studio' using 'Amazon Web Service CodeBuild'

smerc — 1.8.4

Statistical Methods for Regional Counts

smetlite — 0.2.10

Read and Write SMET Files

SMFilter — 1.0.3

Filtering Algorithms for the State Space Models on the Stiefel Manifold

smfishHmrf — 0.1

Hidden Markov Random Field for Spatial Transcriptomic Data

smfsb — 1.5

Stochastic Modelling for Systems Biology

smicd — 1.1.5

Statistical Methods for Interval-Censored Data

smidm — 1.0

Statistical Modelling for Infectious Disease Management

smile — 1.0.5

Spatial Misalignment: Interpolation, Linkage, and Estimation

smiles — 0.1-0

Sequential Method in Leading Evidence Synthesis

smirnov — 1.0-1

Provides two taxonomic coefficients from E. S. Smirnov "Taxonomic analysis" (1969) book

SmithWilsonYieldCurve — 1.1.1

Smith-Wilson Yield Curve Construction

SMITIDstruct — 0.0.5

Data Structure and Manipulations Tool for Host and Viral Population

SMITIDvisu — 0.0.9

Visualize Data for Host and Viral Population from 'SMITIDstruct' using 'HTMLwidgets'

SMLE — 2.1-1

Joint Feature Screening via Sparse MLE

smlePH — 0.1.0

Sieve Maximum Full Likelihood Estimation for the Right-Censored Proportional Hazards Model

smlmkalman — 0.1.1

Generation and Tracking of Super-Resolution Filamentous Datasets

SMLoutliers — 0.1

Outlier Detection Using Statistical and Machine Learning Methods

SMM — 1.0.2

Simulation and Estimation of Multi-State Discrete-Time Semi-Markov and Markov Models

SMMA — 1.0.3

Soft Maximin Estimation for Large Scale Array-Tensor Models

SMME — 1.1.1

Soft Maximin Estimation for Large Scale Heterogeneous Data

smmR — 1.0.3

Simulation, Estimation and Reliability of Semi-Markov Models

SMMT — 1.2.0

The Swiss Municipal Data Merger Tool Maps Municipalities Over Time

SMNCensReg — 3.1

Fitting Univariate Censored Regression Model Under the Family of Scale Mixture of Normal Distributions

smof — 1.2.1

Scoring Methodology for Ordered Factors

smoke — 2.0.1

Small Molecule Octet/BLI Kinetics Experiment

smoof — 1.6.0.3

Single and Multi-Objective Optimization Test Functions

smooth — 4.1.0

Forecasting Using State Space Models

smoothAPC — 0.3

Smoothing of Two-Dimensional Demographic Data, Optionally Taking into Account Period and Cohort Effects

smoothedLasso — 1.6

A Framework to Smooth L1 Penalized Regression Operators using Nesterov Smoothing

smoother — 1.3

Functions Relating to the Smoothing of Numerical Data

SmoothHazard — 2024.04.10

Estimation of Smooth Hazard Models for Interval-Censored Data

smoothHR — 1.0.5

Smooth Hazard Ratio Curves Taking a Reference Value

smoothic — 1.2.0

Variable Selection Using a Smooth Information Criterion

smoothie — 1.0-3

Two-Dimensional Field Smoothing

smoothmest — 0.1-3

Smoothed M-Estimators for 1-Dimensional Location

smoothr — 1.0.1

Smooth and Tidy Spatial Features

smoothROCtime — 0.1.0

Smooth Time-Dependent ROC Curve Estimation

smoothSurv — 2.6

Survival Regression with Smoothed Error Distribution

smoothtail — 2.0.5

Smooth Estimation of GPD Shape Parameter

SmoothTensor — 0.1.1

A Collection of Smooth Tensor Estimation Methods

SmoothWin — 3.0.0

Soft Windowing on Linear Regression

smoothy — 1.0.0

Automatic Estimation of the Most Likely Drug Combination using Smooth Algorithm

smoots — 1.1.4

Nonparametric Estimation of the Trend and Its Derivatives in TS

smosr — 1.0.1

Acquire and Explore BEC-SMOS L4 Soil Moisture Data in R

smotefamily — 1.4.0

A Collection of Oversampling Techniques for Class Imbalance Problem Based on SMOTE

SMOTEWB — 1.2.0

Imbalanced Resampling using SMOTE with Boosting (SMOTEWB)

smovie — 1.1.6

Some Movies to Illustrate Concepts in Statistics

smpic — 0.1.0

Creates Images Sized for Social Media

smplot2 — 0.2.4

Creating Standalone and Composite Plots in 'ggplot2' for Publications

SMPracticals — 1.4-3.1

Practicals for Use with Davison (2003) Statistical Models

SMR — 2.1.0

Externally Studentized Midrange Distribution

sms — 2.3.1

Spatial Microsimulation

sMSROC — 0.1.2

Assessment of Diagnostic and Prognostic Markers

smss — 1.0-2

Datasets for Agresti and Finlay's "Statistical Methods for the Social Sciences"

sMTL — 0.1.0

Sparse Multi-Task Learning

smurf — 1.1.5

Sparse Multi-Type Regularized Feature Modeling

SMUT — 1.1

Multi-SNP Mediation Intersection-Union Test

SMVar — 1.3.4

Structural Model for Variances

smvgraph — 0.1.2

Various Multivariate Graphics with Variable Choice in Shiny Apps

sn — 2.1.1

The Skew-Normal and Related Distributions Such as the Skew-t and the SUN

sna — 2.8

Tools for Social Network Analysis

snahelper — 1.4.2

'RStudio' Addin for Network Analysis and Visualization

Snake — 1.0

Game of Snake

snakecase — 0.11.1

Convert Strings into any Case

SnakesAndLaddersAnalysis — 2.1.0

Play and Analyse the Game of Snakes and Ladders

snap — 1.1.0

Simple Neural Application

snapchatadsR — 0.1.0

Get Snapchat Ads Data via the 'Windsor.ai' API

snapKrig — 0.0.2

Fast Kriging and Geostatistics on Grids with Kronecker Covariance

snapshot — 0.1.2

Gadget N-body cosmological simulation code snapshot I/O utilities

SNBdata — 0.2.1

Download Data from the Swiss National Bank (SNB)

snem — 0.1.1

EM Algorithm for Multivariate Skew-Normal Distribution with Overparametrization

snfa — 0.0.1

Smooth Non-Parametric Frontier Analysis

SNFtool — 2.3.1

Similarity Network Fusion

snha — 0.1.3

Creating Correlation Networks using St. Nicolas House Analysis

snn — 1.1

Stabilized Nearest Neighbor Classifier

snotelr — 1.5.2

Calculate and Visualize 'SNOTEL' Snow Data and Seasonality

snow — 0.4-4

Simple Network of Workstations

SnowballC — 0.7.1

Snowball Stemmers Based on the C 'libstemmer' UTF-8 Library

snowboot — 1.0.2

Bootstrap Methods for Network Inference

snowfall — 1.84-6.3

Easier Cluster Computing (Based on 'snow')

snowflakes — 1.0.0

Random Snowflake Generator

snowFT — 1.6-1

Fault Tolerant Simple Network of Workstations

snowquery — 1.2.1

Query 'Snowflake' Databases with 'SQL'

snpAIMeR — 2.1.1

Assess the Diagnostic Power of Genomic Marker Combinations

SNPannotator — 0.2.6.0

Investigating the Functional Characteristics of Selected SNPs and Their Vicinity Genomic Region

SNPassoc — 2.1-2

SNPs-Based Whole Genome Association Studies

SNPfiltR — 1.0.1

Interactively Filter SNP Datasets

SNPknock — 0.8.2

Knockoffs for Hidden Markov Models and Genetic Data

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