Two- and three-dimensional morphometric maps of enamel and dentine thickness and multivariate analysis. Volume calculation of dental materials. Principal component analysis of thickness maps with associated morphometric map variations.

This package provides a tool to obtain tumor growth rates from clinical trial patient data. Output includes individual and summary data for tumor growth rate estimates as well as optional plots of the observed and predicted tumor quantity over time.

Create rich and fully interactive timeline visualizations. Timelines can be included in Shiny apps or R markdown documents. timevis includes an extensive API to manipulate a timeline after creation, and supports getting data out of the visualization into R. Based on the vis.js Timeline JavaScript library.

This package provides functions are collected to analyse weather data for agriculture purposes including to read weather records in multiple formats, calculate extreme climate index. Demonstration data are included the SILO daily climate data (licensed under CC BY 4.0, <https://www.longpaddock.qld.gov.au/silo/>).

Converting text to numerical features requires specifically created procedures, which are implemented as steps according to the recipes package. These steps allows for tokenization, filtering, counting (tf and tfidf) and feature hashing.

It is a versatile tool for predicting time series data using Long Short-Term Memory (LSTM) models. It is specifically designed to handle time series with an exogenous variable, allowing users to denote whether data was available for a particular period or not. The package encompasses various functionalities, including hyperparameter tuning, custom loss function support, model evaluation, and one-step-ahead forecasting. With an emphasis on ease of use and flexibility, it empowers users to explore, evaluate, and deploy LSTM models for accurate time series predictions and forecasting in diverse applications. More details can be found in Garai and Paul (2023) <doi:10.1016/j.iswa.2023.200202>.

This package provides a tidy workflow for generating, estimating, reporting, and plotting structural equation models using lavaan', OpenMx', or Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as tidy data, making them easy to customize. Includes functionality to estimate latent class analyses, and to plot dagitty and igraph objects.

This package implements an Entropy measure of dependence based on the Bhattacharya-Hellinger-Matusita distance. Can be used as a (nonlinear) autocorrelation/crosscorrelation function for continuous and categorical time series. The package includes tests for serial and cross dependence and nonlinearity based on it. Some routines have a parallel version that can be used in a multicore/cluster environment. The package makes use of S4 classes.

Cleans spectrophotometry data obtained from the Denovix instrument. The package also provides an option to normalize the data in order to compare the quality of the samples obtained.

This package provides an interactive interface to the tfrmt package. Users can import, modify, and export tables and templates with little to no code.

This package implements tic-tac-toe game to play on console, either with human or AI players. Various levels of AI players are trained through the Q-learning algorithm.

Better looking call stacks after an error.

The Time-Delay Correlation algorithm (TDCor) reconstructs the topology of a gene regulatory network (GRN) from time-series transcriptomic data. The algorithm is described in details in Lavenus et al., Plant Cell, 2015. It was initially developed to infer the topology of the GRN controlling lateral root formation in Arabidopsis thaliana. The time-series transcriptomic dataset which was used in this study is included in the package to illustrate how to use it.

This package provides a user friendly interface to generation of booktab style tables using xtable'.

This package provides a suite of functions for visualising ternary probabilistic forecasts, as discussed in the paper by Jupp (2012) <doi:10.1098/rsta.2011.0350>.

This package provides a coherent interface to multiple modelling tools for fitting trends along with a standardised approach for generating confidence and prediction intervals.

This package provides test statistics, p-value, and confidence intervals based on 9 hypothesis tests for dependence.

This package provides tools to perform multiple comparison analyses, based on the well-known Tukey's "Honestly Significant Difference" (HSD) test. In models involving interactions, TukeyC stands out from other R packages by implementing intuitive and easy-to-use functions. In addition to accommodating traditional R methods such as lm() and aov(), it has also been extended to objects of the lmer() class, that is, mixed models with fixed effects. For more details see Tukey (1949) <doi:10.2307/3001913>.

Extract trends from monthly and quarterly economic time series. Provides two main functions: augment_trends() for pipe-friendly tibble workflows and extract_trends() for direct time series analysis. Includes key econometric filters and modern parameter experimentation tools.

This package provides functions to access historical and real-time national hydrometric data from Water Survey of Canada data sources and then applies tidy data principles.

Flexible and ergonomic topological sorting implementation for R. Supports a variety of input data encoding (lists of edges or adjacency matrices, graphs edge direction), stable sort variants as well as cycle detection with detailed diagnosis.

This package provides a set of tools for managing time-series data, with a particular emphasis on defining various frequency types such as daily and weekly. It also includes functionality for converting data between different frequencies.

Utilities for text analysis.

Goodness of Fit and Forecast Evaluation Tests for timeseries models. Includes, among others, the Generalized Method of Moments (GMM) Orthogonality Test of Hansen (1982), the Nyblom (1989) parameter constancy test, the sign-bias test of Engle and Ng (1993), and a range of tests for value at risk and expected shortfall evaluation.