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ClustTMB

spatial finite mixture model R package

Install / Use

/learn @Andrea-Havron/ClustTMB
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

<!-- README.md is generated from README.Rmd. Please edit that file -->

clustTMB

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clustTMB fits finite mixture models that incorporate both covariate and random effect structure within either the gating, the expert, or both components of the model. The clustTMB model is built in Template Model Builder (TMB) and implemented in R using formula syntax similar to other finite mixture modeling packages such as mclust. The TMB structure of the finite mixture model allows for fast computations of random effects by using the Laplace Approximation to calculate the marginal likelihood of fixed effects after integrating out random components. Spatial random effects are estimated through approximations of the Gaussian Markov Random Fields via the FEM-SPDE method introduced by INLA.

Installation

You can install the development version from GitHub with:

remotes::install_github("Andrea-Havron/clustTMB", build_vignettes = TRUE)

Example

A basic example is illustrated with the faithful dataset:

library(clustTMB)
data("faithful")
m1 <- clustTMB(response = faithful, covariance.structure = "VVV")
<img src="man/figures/README-run-example-1.png" width="100%" />

Vignettes

For more detailed examples, see vignettes:

## Not Run

# install.packages("utils")
utils::browseVignettes("clustTMB")

## End Not Run
View on GitHub
GitHub Stars5
CategoryDevelopment
Updated9mo ago
Forks1

Languages

R

Security Score

62/100

Audited on Jun 11, 2025

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