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Complete Environment for Bayesian Inference

Provides a complete environment for Bayesian inference using a variety of different samplers (see ?LaplacesDemon for an overview).

A Framework for Robust Shiny Applications

An opinionated framework for building a production-ready 'Shiny' application. This package contains a series of tools for building a robust 'Shiny' application from start to finish.

Nelson-Aalen Estimator of the Cumulative Hazard in Multistate Models

Computes the Nelson-Aalen estimator of the cumulative transition hazard for arbitrary Markov multistate models

Statistical Pattern Recognition and daTing using Archaeological Artefacts assemblageS

Statistical pattern recognition and dating using archaeological artefacts assemblages.
Package of statistical tools for archaeology.
hclustcompro(perioclust): Bellanger Lise, Coulon Arthur, Husi Philippe (2021, ISBN:978-3-030-60103-4).
mapclust: Bellanger Lise, Coulon Arthur, Husi Philippe (2021)

Empirical Transition Matrix

The etm (empirical transition matrix) package permits to estimate the matrix of transition probabilities for any time-inhomogeneous multi-state model with finite state space using the Aalen-Johansen estimator. Functions for data preparation and for displaying are also included (Allignol et al., 2011

Clustering and Prediction using Multi-Task Gaussian Processes with Common Mean

An implementation for the multi-task Gaussian processes with common
mean framework. Two main algorithms, called 'Magma' and 'MagmaClust',
are available to perform predictions for supervised learning problems, in
particular for time series or any functional/continuous data applications.
The corresponding articles has been respectively proposed by Arthur Leroy,
Pierre Latouche, Benjamin Guedj and Servane Gey (2022)

Auxiliary Data Package for Our Main Package 'dartR'

Data package for 'dartR'. Provides data sets to run examples in 'dartR'. This was necessary due to the size limit imposed by 'CRAN'. The data in 'dartR.data' is needed to run the examples provided in the 'dartR' functions. All available data sets are either based on actual data (but reduced in size) and/or simulated data sets to allow the fast execution of examples and demonstration of the functions.

Bayesian Latent Class Analysis

Bayesian Latent Class Analysis using several different methods.

Bayesian Statistical Tools for Quantitative Proteomics

Bayesian toolbox for quantitative proteomics. In particular, this
package provides functions to generate synthetic datasets, execute Bayesian
differential analysis methods, and display results as, described in the
associated article Marie Chion and Arthur Leroy (2023)

Interaction with "RevBayes" in R

Interaction with "RevBayes" via R. Objects created in "RevBayes" can be passed into the R environment, and many types can be converted into similar R objects. To download "RevBayes", go to < https://revbayes.github.io/download>.