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DIFM

Dynamic ICAR Spatiotemporal Factor Models

v1.0.1 · Nov 11, 2025 · GPL (>= 2)

Description

Bayesian factor models are effective tools for dimension reduction. This is especially applicable to multivariate large-scale datasets. It allows researchers to understand the latent factors of the data which are the linear or non-linear combination of the variables. Dynamic Intrinsic Conditional Autocorrelative Priors (ICAR) Spatiotemporal Factor Models 'DIFM' package provides function to run Markov Chain Monte Carlo (MCMC), evaluation methods and visual plots from Shin and Ferreira (2023)<doi:10.1016/j.spasta.2023.100763>. Our method is a class of Bayesian factor model which can account for spatial and temporal correlations. By incorporating these correlations, the model can capture specific behaviors and provide predictions.

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NOTE r-oldrel-macos-arm64

installed package size

  installed size is  6.8Mb
  sub-directories of 1Mb or more:
    libs   6.2Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  6.9Mb
  sub-directories of 1Mb or more:
    libs   6.3Mb
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

installed package size

  installed size is  6.8Mb
  sub-directories of 1Mb or more:
    libs   6.2Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  6.9Mb
  sub-directories of 1Mb or more:
    libs   6.3Mb

Dependency Network

Dependencies Reverse dependencies Rcpp Matrix LaplacesDemon spdep gridExtra sp DIFM

Version History

new 1.0.1 Mar 9, 2026