All packages

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sudachir — 0.1.0

R Interface to 'Sudachi'

suddengains — 0.7.2

Identify Sudden Gains in Longitudinal Data

sudoku — 2.8

Sudoku Puzzle Generator and Solver

sudokuAlt — 0.2-1

Tools for Making and Spoiling Sudoku Games

SudokuDesigns — 1.1.0

Sudoku as an Experimental Design

SuessR — 0.1.6

Suess and Laws Corrections for Marine Stable Carbon Isotope Data

sufficientForecasting — 0.1.0

Sufficient Forecasting using Factor Models

sugarbag — 0.1.6

Create Tessellated Hexagon Maps

sugarglider — 1.0.3

Create Glyph-Maps of Spatiotemporal Data

suggests — 0.1.0

Declare when Suggested Packages are Needed

sugrrants — 0.2.9

Supporting Graphs for Analysing Time Series

SumcaVer1 — 0.1.0

Mean Square Prediction Error Estimation in Small Area Estimation

sumFREGAT — 1.2.5

Fast Region-Based Association Tests on Summary Statistics

summariser — 2.3.0

Easy Calculation and Visualisation of Confidence Intervals

SummaryLasso — 1.2.1

Building Polygenic Risk Score Using GWAS Summary Statistics

summarytools — 1.1.1

Tools to Quickly and Neatly Summarize Data

summclust — 0.7.2

Module to Compute Influence and Leverage Statistics for Regression Models with Clustered Errors

SUMMER — 2.0.0

Small-Area-Estimation Unit/Area Models and Methods for Estimation in R

SUMO — 0.1.0

Generating Multi-Omics Datasets

sumR — 0.4.15

Approximate Summation of Series

sumSome — 1.1.0

Permutation True Discovery Guarantee by Sum-Based Tests

sunburstR — 2.1.8

Sunburst 'Htmlwidget'

suncalc — 0.5.1

Compute Sun Position, Sunlight Phases, Moon Position and Lunar Phase

SunCalcMeeus — 0.1.2

Sun Position and Daylight Calculations

Sunclarco — 1.0.0

Survival Analysis using Copulas

sundialr — 0.1.6.2

An Interface to 'SUNDIALS' Ordinary Differential Equation (ODE) Solvers

SUNGEO — 1.3.0

Sub-National Geospatial Data Archive: Geoprocessing Toolkit

SunsVoc — 0.1.2

Constructing Suns-Voc from Outdoor Time-Series I-V Curves

suntools — 1.0.1

Calculate Sun Position, Sunrise, Sunset, Solar Noon and Twilight

supclust — 1.1-1

Supervised Clustering of Predictor Variables Such as Genes

super — 0.1.0

Interpreted String Literals

superb — 0.95.19

Summary Plots with Adjusted Error Bars

superbiclust — 1.2

Generating Robust Biclusters from a Bicluster Set (Ensemble Biclustering)

SuperCell — 1.0.1

Simplification of scRNA-Seq Data by Merging Together Similar Cells

supercells — 1.0.0

Superpixels of Spatial Data

supercompress — 1.1

Supervised Compression of Big Data

superdiag — 2.0

A Comprehensive Test Suite for Testing Markov Chain Nonconvergence

SuperExactTest — 1.1.0

Exact Test and Visualization of Multi-Set Intersections

SuperGauss — 2.0.3

Superfast Likelihood Inference for Stationary Gaussian Time Series

superheat — 0.1.0

A Graphical Tool for Exploring Complex Datasets Using Heatmaps

SuperLearner — 2.0-29

Super Learner Prediction

superMICE — 1.1.1

SuperLearner Method for MICE

superml — 0.5.7

Build Machine Learning Models Like Using Python's Scikit-Learn Library in R

supernova — 3.0.0

Judd, McClelland, & Ryan Formatting for ANOVA Output

superpc — 1.12

Supervised Principal Components

SuperpixelImageSegmentation — 1.0.5

Superpixel Image Segmentation

Superpower — 0.2.0

Simulation-Based Power Analysis for Factorial Designs

SuperRanker — 1.2.1

Sequential Rank Agreement

superspreading — 0.3.0

Understand Individual-Level Variation in Infectious Disease Transmission

supervisedPRIM — 2.0.0

Supervised Classification Learning and Prediction using Patient Rule Induction Method (PRIM)

SupMZ — 0.2.0

Detecting Structural Change with Heteroskedasticity

SuppDists — 1.1-9.8

Supplementary Distributions

support.BWS — 0.4-6

Tools for Case 1 Best-Worst Scaling

support.BWS2 — 0.4-0

Tools for Case 2 Best-Worst Scaling

support.BWS3 — 0.2-1

Tools for Case 3 Best-Worst Scaling

support.CEs — 0.7-0

Basic Functions for Supporting an Implementation of Choice Experiments

supportR — 1.4.0

Support Functions for Wrangling and Visualization

sur — 1.0.4

Companion to "Statistics Using R: An Integrative Approach"

surbayes — 0.1.2

Bayesian Analysis of Seemingly Unrelated Regression Models

sure — 0.2.0

Surrogate Residuals for Ordinal and General Regression Models

sureLDA — 0.1.0-1

A Novel Multi-Disease Automated Phenotyping Method for the EHR

SuRF.vs — 1.1.0.1

Subsampling Ranking Forward Selection (SuRF)

surface — 0.6

Fitting Hansen Models to Investigate Convergent Evolution

SurfaceTortoise — 2.0.1

Find Optimal Sampling Locations Based on Spatial Covariate(s)

SurfRough — 0.0.1.0

Calculate Surface/Image Texture Indexes

surreal — 0.0.1

Create Datasets with Hidden Images in Residual Plots

Surrogate — 3.3.3

Evaluation of Surrogate Endpoints in Clinical Trials

SurrogateBMA — 1.0

Flexible Evaluation of Surrogate Markers with Bayesian Model Averaging

SurrogateOutcome — 1.1

Estimation of the Proportion of Treatment Effect Explained by Surrogate Outcome Information

SurrogateParadoxTest — 2.0

Empirical Testing of Surrogate Paradox Assumptions

SurrogateRank — 1.0

Rank-Based Test to Evaluate a Surrogate Marker

SurrogateRegression — 0.6.0.1

Surrogate Outcome Regression Analysis

SurrogateRsq — 0.2.1

Goodness-of-Fit Analysis for Categorical Data using the Surrogate R-Squared

SurrogateSeq — 1.0

Group Sequential Testing of a Treatment Effect Using a Surrogate Marker

SurrogateTest — 1.3

Early Testing for a Treatment Effect using Surrogate Marker Information

surrosurv — 1.1.26

Evaluation of Failure Time Surrogate Endpoints in Individual Patient Data Meta-Analyses

surrosurvROC — 0.1.0

Surrogate Survival ROC

surtvep — 1.0.0

Cox Non-Proportional Hazards Model with Time-Varying Coefficients

surv2sampleComp — 1.0-5

Inference for Model-Free Between-Group Parameters for Censored Survival Data

survAH — 1.0.0

Survival Data Analysis using Average Hazard

survAUC — 1.3-0

Estimators of Prediction Accuracy for Time-to-Event Data

survAWKMT2 — 1.0.1

Two-Sample Tests Based on Differences of Kaplan-Meier Curves

survBootOutliers — 1.0

Concordance Based Bootstrap Methods for Outlier Detection in Survival Analysis

survC1 — 1.0-3

C-Statistics for Risk Prediction Models with Censored Survival Data

survcompare — 0.2.0

Nested Cross-Validation to Compare Cox-PH, Cox-Lasso, Survival Random Forests

SurvCorr — 1.1

Correlation of Bivariate Survival Times

survCurve — 1.0

Plots Survival Curves Element by Element

SurvDisc — 0.1.1

Discrete Time Survival and Longitudinal Data Analysis

surveil — 0.3.0

Time Series Models for Disease Surveillance

surveillance — 1.24.1

Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

survELtest — 2.0.1

Comparing Multiple Survival Functions with Crossing Hazards

SurvEval — 1.1

Methods for the Evaluation of Survival Models

survex — 1.2.0

Explainable Machine Learning in Survival Analysis

survexp.fr — 1.1

Relative Survival, AER and SMR Based on French Death Rates

survey — 4.4-2

Analysis of Complex Survey Samples

surveybootstrap — 0.0.3

Bootstrap with Survey Data

SurveyCC — 0.2.1

Canonical Correlation for Survey Data

surveyCV — 0.2.0

Cross Validation Based on Survey Design

surveydata — 0.2.7

Tools to Work with Survey Data

SurveyDefense — 0.2.0

Survey Defense Tool

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