mclust - Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.
Last updated 7 months ago
12.69 score 20 stars 584 packages 6.4k scripts 73k downloads
GA - Genetic Algorithms
Flexible general-purpose toolbox implementing genetic algorithms (GAs) for stochastic optimisation. Binary, real-valued, and permutation representations are available to optimize a fitness function, i.e. a function provided by users depending on their objective function. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach. For more details see Scrucca (2013) <doi:10.18637/jss.v053.i04> and Scrucca (2017) <doi:10.32614/RJ-2017-008>.
Last updated 2 months ago
genetic-algorithmoptimisation
11.77 score 91 stars 51 packages 580 scripts 7.3k downloadsqcc - Quality Control Charts
Shewhart quality control charts for continuous, attribute and count data. Cusum and EWMA charts. Operating characteristic curves. Process capability analysis. Pareto chart and cause-and-effect chart. Multivariate control charts.
Last updated 2 years ago
11.02 score 43 stars 6 packages 734 scripts 12k downloadsclustvarsel - Variable Selection for Gaussian Model-Based Clustering
Variable selection for Gaussian model-based clustering as implemented in the 'mclust' package. The methodology allows to find the (locally) optimal subset of variables in a data set that have group/cluster information. A greedy or headlong search can be used, either in a forward-backward or backward-forward direction, with or without sub-sampling at the hierarchical clustering stage for starting 'mclust' models. By default the algorithm uses a sequential search, but parallelisation is also available.
Last updated 4 years ago
4.01 score 1 packages 34 scripts 436 downloadsppgmmga - Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms
Projection Pursuit (PP) algorithm for dimension reduction based on Gaussian Mixture Models (GMMs) for density estimation using Genetic Algorithms (GAs) to maximise an approximated negentropy index. For more details see Scrucca and Serafini (2019) <doi:10.1080/10618600.2019.1598871>.
Last updated 2 months ago
4.00 score 2 stars 8 scripts 182 downloadsmsir - Model-Based Sliced Inverse Regression
An R package for dimension reduction based on finite Gaussian mixture modeling of inverse regression.
Last updated 4 years ago
3.23 score 42 scripts 315 downloadsmclustAddons - Addons for the 'mclust' Package
Extend the functionality of the 'mclust' package for Gaussian finite mixture modeling by including: density estimation for data with bounded support (Scrucca, 2019 <doi:10.1002/bimj.201800174>); modal clustering using MEM (Modal EM) algorithm for Gaussian mixtures (Scrucca, 2021 <doi:10.1002/sam.11527>); entropy estimation via Gaussian mixture modeling (Robin & Scrucca, 2023 <doi:10.1016/j.csda.2022.107582>).
Last updated 2 months ago
3.00 score 7 scripts 374 downloadsdispmod - Modelling Dispersion in GLM
Functions for estimating Gaussian dispersion regression models (Aitkin, 1987 <doi:10.2307/2347792>), overdispersed binomial logit models (Williams, 1987 <doi:10.2307/2347977>), and overdispersed Poisson log-linear models (Breslow, 1984 <doi:10.2307/2347661>), using a quasi-likelihood approach.
Last updated 7 years ago
1.95 score 18 scripts 187 downloads