An RStudio addin providing shortcuts for writing in Markdown'. This package provides a series of functions that allow the user to be more efficient when using Markdown'. For example, you can select a word, and put it in bold or in italics, or change the alignment of elements inside you Rmd. The idea is to map all the functionalities from remedy on keyboard shortcuts, so that it provides an interface close to what you can find in any other text editor.

Create plots and LaTeX tables that look like SPSS output for use in teaching materials. Rather than copying-and-pasting SPSS output into documents, R code that mocks up SPSS output can be integrated directly into dynamic LaTeX documents with tools such as knitr. Functionality includes statistical techniques that are typically covered in introductory statistics classes: descriptive statistics, common hypothesis tests, ANOVA, and linear regression, as well as box plots, histograms, scatter plots, and line plots (including profile plots).

It extends the functionality of logger package. Additional logging metadata can be configured to be collected. Logging messages are displayed on console and optionally they are sent to Azure Log Analytics workspace in real-time.

The Cauchy Process can model pulsed continuous trait evolution on phylogenies. The likelihood is tractable, and is used for parameter inference and ancestral trait reconstruction. See Bastide and Didier (2023) <doi:10.1093/sysbio/syad053>.

Psychometrically analyze latent individual differences related to tasks, interventions, or maturational/aging effects in the context of experimental or longitudinal cognitive research using methods first described by Thomas et al. (2020) <doi:10.1177/0013164420919898>.

Create rich command line applications, with colors, headings, lists, alerts, progress bars, etc. It uses CSS for custom themes. This package is now superseded by the cli package. Please use cli instead in new projects.

An engine for stochastic cellular automata. It provides a high-level interface to declare a model, which can then be simulated by various backends (Genin et al. (2023) <doi:10.1101/2023.11.08.566206>).

Fatty acid metabolic analysis aimed to the estimation of FA import (I), de novo synthesis (S), fractional contribution of the 13C-tracers (D0, D1, D2), elongation (E) and desaturation (Des) based on mass isotopologue data.

This package provides an interface to the Instagram API <https://instagram.com/ developer/>, which allows R users to download public pictures filtered by hashtag, popularity, user or location, and to access public users profile data.

This package provides an estimator for generalized linear models with incomplete data for discrete covariates. The estimation is based on the EM algorithm by the method of weights by Ibrahim (1990) <DOI:10.2307/2290013>.

Implementation of joint sparse optimization (JSparO) to infer the gene regulatory network for cell fate conversion. The proximal gradient method is implemented to solve different low-order regularization models for JSparO.

The goal of kronos is to provide an easy-to-use framework to analyse circadian or otherwise rhythmic data using the familiar R linear modelling syntax, while taking care of the trigonometry under the hood.

This package provides function for the l1-ball prior on high-dimensional regression. The main function, l1ball(), yields posterior samples for linear regression, as introduced by Xu and Duan (2020) <arXiv:2006.01340>.

This package provides tools for detecting and correcting sample mix-ups between two sets of measurements, such as between gene expression data on two tissues. Broman et al. (2015) <doi:10.1534/g3.115.019778>.

Highly variable gene selection methods, including popular public available methods, and also the mixture of multiple highly variable gene selection methods, <https://github.com/RuzhangZhao/mixhvg>. Reference: <doi:10.1101/2024.08.25.608519>.

This function allows to generate two biological conditions synthetic microarray dataset which has similar behavior to those currently observed with common platforms. User provides a subset of parameters. Available default parameters settings can be modified.

The main function MMEst() performs (Restricted) Maximum Likelihood in a variance component mixed models using a Min-Max (MM) algorithm (Laporte, F., Charcosset, A. & Mary-Huard, T. (2022) <doi:10.1371/journal.pcbi.1009659>).

Allows to perform the multivariate version of the Diebold-Mariano test for equal predictive ability of multiple forecast comparison. Main reference: Mariano, R.S., Preve, D. (2012) <doi:10.1016/j.jeconom.2012.01.014>.

Developed for model-based clustering using the finite mixtures of skewed sub-Gaussian stable distributions developed by Teimouri (2022) <arXiv:2205.14067> and estimating parameters of the symmetric stable distribution within the Bayesian framework.

Allows users to simulate matrix population models with particular characteristics based on aspects of life history such as mortality trajectories and fertility trajectories. Also allows the exploration of sampling error due to small sample size.

Dirichlet process mixture of multivariate normal, skew normal or skew t-distributions modeling oriented towards flow-cytometry data preprocessing applications. Method is detailed in: Hejblum, Alkhassimn, Gottardo, Caron & Thiebaut (2019) <doi: 10.1214/18-AOAS1209>.

This package provides functions to compute and plot power levels, minimum detectable effect sizes, and minimum required sample sizes for the test of the overall average effect size in meta-analysis of dependent effect sizes.

M-estimator for threshold and non-threshold spatial dynamic panel data model. Yang, Z (2018) <doi:10.1016/j.jeconom.2017.08.019>. Wu, J., Matsuda, Y (2021) <doi:10.1007/s43071-021-00008-1>.

Simulates data from model objects (e.g., from lm(), glm()), and plots this along with the original data to compare how well the simulated data matches the original data to determine model fit.