Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 35 packages in 0.01 seconds

LaplacesDemon — by Henrik Singmann, a year ago

Complete Environment for Bayesian Inference

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

SPARTAAS — by Arthur Coulon, a year ago

Statistical Methods for Archaeology

Statistical pattern recognition and dating using archaeological artefacts assemblages. Package of statistical tools for archaeology. hclustcompro(perioclust): Bellanger Lise, Coulon Arthur, Husi Philippe (2020, ISBN:978-3-030-60103-4). mapclust: Bellanger Lise, Coulon Arthur, Husi Philippe (2021) . seriograph: Desachy Bruno (2004) .

RGCCA — by Arthur Tenenhaus, 5 years ago

Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock Data

Multiblock 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: (i) to study the relationships between blocks and (ii) to identify subsets of variables of each block which are active in their relationships with the other blocks.

BayesLCA — by Arthur White, 2 years ago

Bayesian Latent Class Analysis

Bayesian Latent Class Analysis using several different methods.

ChainLadder — by Markus Gesmann, a month ago

Statistical Methods and Models for Claims Reserving in General Insurance

Various statistical methods and models which are typically used for the estimation of outstanding claims reserves in general insurance, including those to estimate the claims development result as required under Solvency II.

etm — by Mark Clements, 2 years ago

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 ).

MagmaClustR — by Arthur Leroy, a month ago

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 (2020) . 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.

Revticulate — by Caleb Charpentier, 6 months ago

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>.

mvna — by Arthur Allignol, 5 years ago

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 .

Cprob — by Arthur Allignol, 4 years ago

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 .