All packages

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troopdata — 1.0.0

Tools for Analyzing Cross-National Military Deployment and Basing Data

tropAlgebra — 0.1.1

Tropical Algebraic Functions

TropFishR — 1.6.4

Tropical Fisheries Analysis

trotter — 0.6

Pseudo-Vectors Containing All Permutations, Combinations and Subsets of Objects Taken from a Vector.

trouBBlme4SolveR — 0.1.1

Troubles Solver for 'lme4'

TroublemakeR — 0.0.1

Generates Spatial Problems in R for 'AMPL'

TrtCombo.FactorialExp.SR — 4.0.4

Generation of Treatment Combination (in Standard Order) in 2^n Factorial Experiment

trtf — 0.4-2

Transformation Trees and Forests

truelies — 0.2.0

Bayesian Methods to Estimate the Proportion of Liars in Coin Flip Experiments

TrueSkillThroughTime — 0.1.1

Skill Estimation Based on a Single Bayesian Network

truh — 1.0.0

Two-Sample Nonparametric Testing Under Heterogeneity

TrumpetPlots — 0.0.1.1

Visualization of Genetic Association Studies

truncAIPW — 1.0.1

Doubly Robust Estimation under Covariate-Induced Dependent Left Truncation

TruncatedNormal — 2.2.2

Truncated Multivariate Normal and Student Distributions

truncdist — 1.0-2

Truncated Random Variables

TruncExpFam — 1.1.1

Truncated Exponential Family

truncnorm — 1.0-9

Truncated Normal Distribution

truncnormbayes — 0.0.3

Estimates Moments for a Truncated Normal Distribution using 'Stan'

truncreg — 0.2-5

Truncated Gaussian Regression Models

truncSP — 1.2.2

Semi-parametric estimators of truncated regression models

trust — 0.1-8

Trust Region Optimization

trustedtimestamping — 0.2.6

Create Trusted Timestamps of Datasets and Files

trustOptim — 0.8.7.3

Trust Region Optimization for Nonlinear Functions with Sparse Hessians

tryCatchLog — 1.3.1

Advanced 'tryCatch()' and 'try()' Functions

tryr — 0.1.1

Client/Server Error Handling for HTTP API Frameworks

TSA — 1.3.1

Time Series Analysis

tsallisqexp — 0.9-4

Tsallis q-Exp Distribution

TSANN — 0.1.0

Time Series Artificial Neural Network

tsapp — 1.0.4

Time Series, Analysis and Application

tsbox — 0.4.1

Class-Agnostic Time Series

tsBSS — 1.0.0

Blind Source Separation and Supervised Dimension Reduction for Time Series

TSCI — 3.0.4

Tools for Causal Inference with Possibly Invalid Instrumental Variables

TSclust — 1.3.1

Time Series Clustering Utilities

tscopula — 0.3.9

Time Series Copula Models

tscount — 1.4.3

Analysis of Count Time Series

TSCS — 0.1.1

Time Series Cointegrated System

tsdataleaks — 2.1.1

Exploit Data Leakages in Time Series Forecasting Competitions

tsdb — 1.1-0

Terribly-Simple Data Base for Time Series

tsdecomp — 0.2

Decomposition of Time Series Data

TSdeeplearning — 0.1.0

Deep Learning Model for Time Series Forecasting

tsdf — 1.1-8

Two-/Three-Stage Designs for Phase 1&2 Clinical Trials

TSDFGS — 2.0

Training Set Determination for Genomic Selection

tsdisagg2 — 0.1.0

Time Series Disaggregation

TSdisaggregation — 2.0.0

High-Dimensional Temporal Disaggregation

TSdist — 3.7.1

Distance Measures for Time Series Data

tsdistributions — 1.0.1

Location Scale Standardized Distributions

TSDT — 1.0.7

Treatment-Specific Subgroup Detection Tool

tsDyn — 11.0.4.1

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 — 0.10-56

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 — 0.3-4

Analysis of Nonlinear Time Series Through 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 — 1.0.2

Univariate GARCH Models

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 — 1.1.5

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

TSLSTM — 0.1.0

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

TSLSTMplus — 1.0.4

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

tsmethods — 1.0.1

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 — 0.3.5

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 — 1.2-4

Traveling Salesperson Problem (TSP)

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 — 1.0.767

Time Series Prediction 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 — 0.1.7

Simulation of Daily and Monthly Time Series

TSsmoothing — 0.1.0

Trend Estimation of Univariate and Bivariate Time Series with Controlled Smoothness

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