Spatio-Temporal Finite Mixture Model using 'TMB'

Fits a spatio-temporal finite mixture model using 'TMB'. Covariate, spatial and temporal random effects can be incorporated into the gating formula using multinomial logistic regression, the expert formula using a generalized linear mixed model framework, or both.

clustTMB

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")

Vignettes

For more detailed examples, see vignettes:

• Available Covariance Structures
• Spatial Example

## Not Run

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

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