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) . seriograph: Desachy Bruno (2004) . cerardat: Bellanger Lise, Husi Philippe (2012) .

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) , and Arthur Leroy, Pierre Latouche, Benjamin Guedj and Servane Gey (2023) < https://jmlr.org/papers/v24/20-1321.html>. Theses approaches leverage the learning of cluster-specific mean processes, which are common across similar tasks, to provide enhanced prediction performances (even far from data) at a linear computational cost (in the number of tasks). 'MagmaClust' is a generalisation of 'Magma' where the tasks are simultaneously clustered into groups, each being associated to a specific mean process. User-oriented functions in the package are decomposed into training, prediction and plotting functions. Some basic features (classic kernels, training, prediction) of standard Gaussian processes are also implemented.

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 ). Functionals of the Aalen-Johansen estimator, e.g., excess length-of-stay in an intermediate state, can also be computed (Allignol et al. 2011 ).

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>.

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) .

The Conditional Probability Function of a Competing Event

Permits to estimate the conditional probability function of a competing event, and to fit, using the temporal process regression or the pseudo-value approach, a proportional-odds model to the conditional probability function (or other models by specifying another link function). See .

Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock Data

Multi-block data analysis concerns the analysis of several sets of variables (blocks) observed on the same group of individuals. The main aims of the RGCCA package are: to study the relationships between blocks and to identify subsets of variables of each block which are active in their relationships with the other blocks. This package allows to (i) run R/SGCCA and related methods, (ii) help the user to find out the optimal parameters for R/SGCCA such as regularization parameters (tau or sparsity), (iii) evaluate the stability of the RGCCA results and their significance, (iv) build predictive models from the R/SGCCA. (v) Generic print() and plot() functions apply to all these functionalities.

Communication Between Editor and Viewer for Literate Programs

This utility eases the debugging of literate documents ('noweb' files) by patching the synchronization information (the '.synctex(.gz)' file) produced by 'pdflatex' with concordance information produced by 'Sweave' or 'knitr' and 'Sweave' or 'knitr' ; this allows for bilateral communication between a text editor (visualizing the 'noweb' source) and a viewer (visualizing the resultant 'PDF'), thus bypassing the intermediate 'TeX' file.