All packages

· A · B · C · D · E · F · G · H · I · J · K · L · M · N · O · P · Q · R · S · T · U · V · W · X · Y · Z ·

tsDyn — 11.0.5.2

Nonlinear Time Series Models with Regime Switching

TSE — 0.1.0

Total Survey Error

TSEAL — 0.1.3

Time Series Analysis Library

TSEind — 0.1.0

Total Survey Error (Independent Samples)

tsensembler — 0.1.0

Dynamic Ensembles for Time Series Forecasting

tsentiment — 1.0.5

Fetching Tweet Data for Sentiment Analysis

TSEntropies — 0.9

Time Series Entropies

tseries — 0.10-58

Time Series Analysis and Computational Finance

tseriesChaos — 0.1-13.1

Analysis of Nonlinear Time Series

tseriesEntropy — 0.7-2

Entropy Based Analysis and Tests for Time Series

TSeriesMMA — 0.1.1

Multiscale Multifractal Analysis of Time Series Data

tseriesTARMA — 0.5-1

Analysis of Nonlinear Time Series Through Threshold Autoregressive Moving Average Models (TARMA) Models

TSEtools — 0.2.2

Manage Data from Stock Exchange Markets

TSEwgt — 0.1.0

Total Survey Error Under Multiple, Different Weighting Schemes

TSF — 0.1.1

Two Stage Forecasting (TSF) for Long Memory Time Series in Presence of Structural Break

tsfeatures — 1.1.1

Time Series Feature Extraction

tsfgrnn — 1.0.5

Time Series Forecasting Using GRNN

tsfknn — 0.6.0

Time Series Forecasting Using Nearest Neighbors

tsfngm — 0.1.0

Time Series Forecasting using Nonlinear Growth Models

tsgarch — 1.0.3

Univariate GARCH Models

tsgc — 0.0

Time Series Methods Based on Growth Curves

TSGS — 1.0

Trait Specific Gene Selection using SVM and GA

TSGSIS — 0.1

Two Stage-Grouped Sure Independence Screening

TSHRC — 0.1-6

Two Stage Hazard Rate Comparison

tsibble — 1.1.6

Tidy Temporal Data Frames and Tools

tsibbledata — 0.4.1

Diverse Datasets for 'tsibble'

tsibbletalk — 0.1.0

Interactive Graphics for Tsibble Objects

tsintermittent — 1.10

Intermittent Time Series Forecasting

tsiR — 0.4.3

An Implementation of the TSIR Model

tsissm — 1.0.1

Linear Innovations State Space Unobserved Components Model

TSLA — 0.1.2

Tree-Guided Rare Feature Selection and Logic Aggregation

TSLSTM — 0.1.0

Long Short Term Memory (LSTM) Model for Time Series Forecasting

TSLSTMplus — 1.0.6

Long-Short Term Memory for Time-Series Forecasting, Enhanced

tsLSTMx — 0.1.0

Predict Time Series Using LSTM Model Including Exogenous Variable to Denote Zero Values

tsmarch — 1.0.0

Multivariate ARCH Models

tsmethods — 1.0.2

Time Series Methods

TSMN — 1.0.0

Truncated Scale Mixtures of Normal Distributions

tsModel — 0.6-2

Time Series Modeling for Air Pollution and Health

tsmp — 0.4.15

Time Series with Matrix Profile

TSMSN — 0.0.1

Truncated Scale Mixtures of Skew-Normal Distributions

tsna — 0.3.6

Tools for Temporal Social Network Analysis

tsne — 0.1-3.1

T-Distributed Stochastic Neighbor Embedding for R (t-SNE)

tsnet — 0.1.0

Fitting, Comparing, and Visualizing Networks Based on Time Series Data

tsoutliers — 0.6-10

Detection of Outliers in Time Series

TSP — 1.2-5

Infrastructure for the Traveling Salesperson Problem

tsPI — 1.0.4

Improved Prediction Intervals for ARIMA Processes and Structural Time Series

tspmeta — 1.2

Instance Feature Calculation and Evolutionary Instance Generation for the Traveling Salesman Problem

TSPred — 5.1

Functions for Benchmarking Time Series Prediction

tspredit — 1.2.707

Time Series Prediction with Integrated Tuning

tsqn — 1.0.0

Applications of the Qn Estimator to Time Series (Univariate and Multivariate)

TSrepr — 1.1.0

Time Series Representations

tsriadditive — 1.0.0

Two Stage Residual Inclusion Additive Hazards Estimator

tsrobprep — 0.3.2

Robust Preprocessing of Time Series Data

TSS.RESTREND — 0.3.1

Time Series Segmentation of Residual Trends

tsSelect — 0.1.8

Execution of Time Series Models

tssim — 0.2.7

Simulation of Daily and Monthly Time Series

TSsmoothing — 0.1.0

Trend Estimation of Univariate and Bivariate Time Series with Controlled Smoothness

TSSS — 1.3.4-5

Time Series Analysis with State Space Model

TSstudio — 0.1.7

Functions for Time Series Analysis and Forecasting

TSSVM — 0.1.0

Time Series Forecasting using SVM Model

tstests — 1.0.1

Time Series Goodness of Fit and Forecast Evaluation Tests

tstools — 0.4.3

A Time Series Toolbox for Official Statistics

TSTutorial — 1.2.7

Fitting and Predict Time Series Interactive Laboratory

tsutils — 0.9.4

Time Series Exploration, Modelling and Forecasting

TSVC — 1.7.2

Tree-Structured Modelling of Varying Coefficients

tsvio — 1.0.6

Simple Utilities for Tab-Separated-Value (TSV) Files

tsviz — 0.1.0

Easy and Interactive Time Series Visualization

tsvr — 1.0.2

Timescale-Specific Variance Ratio for Use in Community Ecology

tswge — 2.2.0

Time Series for Data Science

tsxtreme — 0.3.4

Bayesian Modelling of Extremal Dependence in Time Series

TTAinterfaceTrendAnalysis — 1.5.10

Temporal Trend Analysis Graphical Interface

ttbary — 0.3-1

Barycenter Methods for Spatial Point Patterns

ttbbeer — 1.1.0

US Beer Statistics from TTB

TTCA — 0.1.1

Transcript Time Course Analysis

ttcg — 1.0.1

Three-Term Conjugate Gradient for Unconstrained Optimization

ttdo — 0.0.10

Extend 'tinytest' with 'diffobj' and 'tinysnapshot'

tth — 4.16-0

TeX-to-HTML/MathML Translators TtH/TtM

tTOlr — 0.2.3

Likelihood Ratio Statistics for One or Two Sample T-Tests

TTR — 0.24.4

Technical Trading Rules

TTR.PGM — 1.0.0

Thornley Transport Resistance Plant Growth Model

TTS — 1.1

Master Curve Estimates Corresponding to Time-Temperature Superposition

ttScreening — 1.6

Genome-Wide DNA Methylation Sites Screening by Use of Training and Testing Samples

ttservice — 0.4.1

A Service for Tidy Transcriptomics Software Suite

ttt — 1.0

The Table Tool

tttplot — 1.1.1

Time to Target Plot

ttutils — 1.0-1.1

Utility Functions

tuber — 1.0.1

Client for the YouTube API

tubern — 0.2.1

R Client for the YouTube Analytics and Reporting API

tuckerR.mmgg — 1.5.1

Three-Mode Principal Components Analysis

TUFLOWR — 0.1.1

Helper Functions for 'TUFLOW FV' Models

tufte — 0.13

Tufte's Styles for R Markdown Documents

tufterhandout — 1.2.1

Tufte-style html document format for rmarkdown

tugboat — 0.1.1

Build a Docker Image from a Directory or Project

TukeyC — 1.3-43

Conventional Tukey Test

TukeyGH77 — 0.1.4

Tukey g-&-h Distribution

tukeytrend — 0.7

Tukeys Trend Test via Multiple Marginal Models

TULIP — 1.0.2

A Toolbox for Linear Discriminant Analysis with Penalties

tumgr — 0.0.4

Tumor Growth Rate Analysis

tune — 1.3.0

Tidy Tuning Tools

TunePareto — 2.5.3

Multi-Objective Parameter Tuning for Classifiers

Next page