All packages

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sehrnett — 0.1.0

A Very Nice Interface to 'WordNet'

SEI — 0.1.1

Calculating Standardised Indices

SEIRfansy — 1.1.1

Extended Susceptible-Exposed-Infected-Recovery Model

seismic — 1.1

Predict Information Cascade by Self-Exciting Point Process

seismicRoll — 1.1.5

Fast Rolling Functions for Seismology using 'Rcpp'

sejmRP — 1.3.4

An Information About Deputies and Votings in Polish Diet from Seventh to Eighth Term of Office

Sejong — 0.01

KoNLP static dictionaries and Sejong project resources.

SEL — 1.0-4

Semiparametric Elicitation

selcorr — 1.0

Post-Selection Inference for Generalized Linear Models

Select — 1.4

Determines Species Probabilities Based on Functional Traits

selectapref — 0.1.2

Analysis of Field and Laboratory Foraging

SelectBoost — 2.2.2

A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets

selection.index — 1.2.0

Analysis of Selection Index in Plant Breeding

SelectionBias — 2.0.0

Calculates Bounds for the Selection Bias for Binary Treatment and Outcome Variables

selectiongain — 2.0.710

A Tool for Calculation and Optimization of the Expected Gain from Multi-Stage Selection

selectiveInference — 1.2.5

Tools for Post-Selection Inference

selectMeta — 1.0.8

Estimation of Weight Functions in Meta Analysis

selectr — 0.4-2

Translate CSS Selectors to XPath Expressions

selectspm — 0.6

Select Point Pattern Models Based on Minimum Contrast, AIC and Goodness of Fit

SeleMix — 1.0.2

Selective Editing via Mixture Models

selenider — 0.4.0

Concise, Lazy and Reliable Wrapper for 'chromote' and 'selenium'

selenium — 0.1.3

Low-Level Browser Automation Interface

seleniumPipes — 0.3.7

R Client Implementing the W3C WebDriver Specification

SELF — 0.1.1

A Structural Equation Embedded Likelihood Framework for Causal Discovery

selfingTree — 0.2

Genotype Probabilities in Intermediate Generations of Inbreeding Through Selfing

sem — 3.1-15

Structural Equation Models

semantic.assets — 1.1.0

Assets for 'shiny.semantic'

semantic.dashboard — 0.2.1

Dashboard with Fomantic UI Support for Shiny

Semblance — 1.1.0

A Data-Driven Similarity Kernel on Probability Spaces

semdrw — 0.1.0

'SEM Shiny'

semds — 0.9-6

Structural Equation Multidimensional Scaling

semEff — 0.6.1

Automatic Calculation of Effects for Piecewise Structural Equation Models

semfindr — 0.1.8

Influential Cases in Structural Equation Modeling

semgram — 0.1.0

Extracting Semantic Motifs from Textual Data

SEMgraph — 1.2.1

Network Analysis and Causal Inference Through Structural Equation Modeling

semhelpinghands — 0.1.11

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 — 2.3.2

Building and Estimating Structural Equation Models

SemiPar — 1.0-4.2

Semiparametic Regression

SemiPar.depCens — 0.1.2

Copula Based Cox Proportional Hazards Models for Dependent Censoring

semlbci — 0.11.2

Likelihood-Based Confidence Interval in 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 — 0.8.1

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 — 2.1.0

Power Analyses for SEM

semptools — 0.2.10

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

semTests — 0.5.0

Goodness-of-Fit Testing for Structural Equation 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 — 1.0.0

Automatic Stacked Ensemble for Regression Tasks

sensemakr — 0.1.4

Sensitivity Analysis Tools for Regression Models

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 — 1.30.0

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 — 0.3.0

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 — 0.7.3

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)

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