All packages

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semgram — 0.1.0

Extracting Semantic Motifs from Textual Data

SEMgraph — 1.2.2

Network Analysis and Causal Inference Through Structural Equation Modeling

semhelpinghands — 0.1.12

Helper Functions for Structural Equation Modeling

semiArtificial — 2.4.1

Generator of Semi-Artificial Data

semicmprskcoxmsm — 0.2.0

Use Inverse Probability Weighting to Estimate Treatment Effect for Semi Competing Risks Data

SemiCompRisks — 3.4

Hierarchical Models for Parametric and Semi-Parametric Analyses of Semi-Competing Risks Data

semicontMANOVA — 0.1-8

Multivariate ANalysis of VAriance with Ridge Regularization for Semicontinuous High-Dimensional Data

SEMID — 0.4.1

Identifiability of Linear Structural Equation Models

semidist — 0.1.0

Measure Dependence Between Categorical and Continuous Variables

SemiEstimate — 1.1.3

Solve Semi-Parametric Estimation by Implicit Profiling

SemiMarkov — 1.4.6

Multi-States Semi-Markov Models

seminr — 2.3.4

Building and Estimating Structural Equation Models

SemiPar — 1.0-4.2

Semiparametic Regression

SemiPar.depCens — 0.1.3

Copula Based Cox Proportional Hazards Models for Dependent Censoring

semlbci — 0.11.2

Likelihood-Based Confidence Interval in Structural Equation Models

semlrtp — 0.1.1

Likelihood Ratio Test P-Values for Structural Equation Models

semmcci — 1.1.4

Monte Carlo Confidence Intervals in Structural Equation Modeling

semmcmc — 0.0.6

Bayesian Structural Equation Modeling in Multiple Omics Data Integration

semnar — 0.8.2

Constructing and Interacting with Databases of Presentations

SemNeT — 1.4.4

Methods and Measures for Semantic Network Analysis

SemNetCleaner — 1.3.4

An Automated Cleaning Tool for Semantic and Linguistic Data

SemNetDictionaries — 0.2.0

Dictionaries for the 'SemNetCleaner' Package

semnova — 0.1-6

Latent Repeated Measures ANOVA

semPlot — 1.1.6

Path Diagrams and Visual Analysis of Various SEM Packages' Output

semPower — 2.1.1

Power Analyses for SEM

semptools — 0.3.1

Customizing Structural Equation Modelling Plots

SEMsens — 1.5.5

A Tool for Sensitivity Analysis in Structural Equation Modeling

semsfa — 1.1

Semiparametric Estimation of Stochastic Frontier Models

semTools — 0.5-6

Useful Tools for Structural Equation Modeling

semtree — 0.9.20

Recursive Partitioning for Structural Equation Models

semver — 0.2.0

'Semantic Versioning V2.0.0' Parser

semverutils — 0.1.0

Semantic Version Utilities

sendgridr — 0.6.1

Mail Sender Using 'Sendgrid' Service

sendigR — 1.0.0

Enable Cross-Study Analysis of 'CDISC' 'SEND' Datasets

sendmailR — 1.4-0

Send Email Using R

sense — 1.1.0

Automatic Stacked Ensemble for Regression Tasks

sensemakr — 0.1.6

Sensitivity Analysis Tools for Regression Models

SensIAT — 0.1.1

Sensitivity Analysis for Irregular Assessment Times

sensibo.sky — 1.0.0

Access to 'Sensibo Sky' API V2 for Air Conditioners Remote Control

sensiPhy — 0.8.5

Sensitivity Analysis for Comparative Methods

sensitivity — 1.30.1

Global Sensitivity Analysis of Model Outputs and Importance Measures

sensitivity2x2xk — 1.01

Sensitivity Analysis for 2x2xk Tables in Observational Studies

sensitivityCalibration — 0.0.1

A Calibrated Sensitivity Analysis for Matched Observational Studies

SensitivityCaseControl — 2.2

Sensitivity Analysis for Case-Control Studies

sensitivityfull — 1.5.6

Sensitivity Analysis for Full Matching in Observational Studies

sensitivitymult — 1.0.2

Sensitivity Analysis for Observational Studies with Multiple Outcomes

sensitivitymv — 1.4.3

Sensitivity Analysis in Observational Studies

sensitivitymw — 2.1

Sensitivity Analysis for Observational Studies Using Weighted M-Statistics

SensMap — 0.7

Sensory and Consumer Data Mapping

sensmediation — 0.3.1

Parametric Estimation and Sensitivity Analysis of Direct and Indirect Effects

sensobol — 1.1.5

Computation of Variance-Based Sensitivity Indices

SensoMineR — 1.27

Sensory Data Analysis

sensory — 1.1

Simultaneous Model-Based Clustering and Imputation via a Progressive Expectation-Maximization Algorithm

SenSpe — 1.3

Estimating Specificity at Controlled Sensitivity, or Vice Versa

sensR — 1.5-3

Thurstonian Models for Sensory Discrimination

SenSrivastava — 2015.6.25.1

Datasets from Sen & Srivastava

senstrat — 1.0.3

Sensitivity Analysis for Stratified Observational Studies

SensusR — 2.3.1

Sensus Analytics

sentencepiece — 0.2.3

Text Tokenization using Byte Pair Encoding and Unigram Modelling

sentiment.ai — 0.1.1

Simple Sentiment Analysis Using Deep Learning

SentimentAnalysis — 1.3-5

Dictionary-Based Sentiment Analysis

sentimentr — 2.9.0

Calculate Text Polarity Sentiment

SenTinMixt — 1.0.0

Parsimonious Mixtures of MSEN and MTIN Distributions

sentometrics — 1.0.0

An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

sentopics — 0.7.4

Tools for Joint Sentiment and Topic Analysis of Textual Data

sentryR — 1.1.2

Send Errors and Messages to Sentry

SEofM — 0.1.0

Standard Error of Measurement

SEPaLS — 0.1.0

Shrinkage for Extreme Partial Least-Squares (SEPaLS)

sEparaTe — 0.3.2

Maximum Likelihood Estimation and Likelihood Ratio Test Functions for Separable Variance-Covariance Structures

separationplot — 1.4

Separation Plots

sephora — 0.1.31

Statistical Estimation of Phenological Parameters

sepkoski — 0.0.1

Sepkoski's Fossil Marine Animal Genera Compendium

seq2R — 2.0.1

Simple Method to Detect Compositional Changes in Genomic Sequences

SeqAlignR — 0.1.1

Sequence Alignment and Visualization Tool

SeqAlloc — 1.0

Sequential Allocation for Prospective Experiments

seqDesign — 1.2

Simulation and Group Sequential Monitoring of Randomized Two-Stage Treatment Efficacy Trials with Time-to-Event Endpoints

SeqDetect — 1.0.7

Sequence and Latent Process Detector

SeqExpMatch — 0.1.0

Sequential Experimental Design via Matching on-the-Fly

SeqFeatR — 0.3.1

A Tool to Associate FASTA Sequences and Features

seqgendiff — 1.2.4

RNA-Seq Generation/Modification for Simulation

seqhandbook — 0.1.1

Miscellaneous Tools for Sequence Analysis

seqHMM — 1.2.6

Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series

seqICP — 1.1

Sequential Invariant Causal Prediction

seqimpute — 2.1.0

Imputation of Missing Data in Sequence Analysis

seqinr — 4.2-36

Biological Sequences Retrieval and Analysis

SeqKat — 0.0.8

Detection of Kataegis

SeqMADE — 1.0

Network Module-Based Model in the Differential Expression Analysis for RNA-Seq

seqmagick — 0.1.7

Sequence Manipulation Utilities

seqminer — 9.7

Efficiently Read Sequence Data (VCF Format, BCF Format, METAL Format and BGEN Format) into R

seqmon — 2.5

Group Sequential Design Class for Clinical Trials

SeqNet — 1.1.3

Generate RNA-Seq Data from Gene-Gene Association Networks

seqSHP — 0.1.1

Building Sequences from SHP Waves

seqtest — 0.1-0

Sequential Triangular Test

seqtrie — 0.2.8

Radix Tree and Trie-Based String Distances

SequenceSpikeSlab — 1.0.1

Exact Bayesian Model Selection Methods for the Sparse Normal Sequence Model

Sequential — 4.3.4

Exact Sequential Analysis for Poisson and Binomial Data

SequentialDesign — 1.0

Observational Database Study Planning using Exact Sequential Analysis for Poisson and Binomial Data

sequoia — 2.11.2

Pedigree Inference from SNPs

sergeant — 0.9.1

Tools to Transform and Query Data with Apache Drill

serial — 3.0

The Serial Interface Package

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