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spBFA  

Spatial Bayesian Factor Analysis
View on CRAN: Click here


Download and install spBFA package within the R console
Install from CRAN:
install.packages("spBFA")

Install from Github:
library("remotes")
install_github("cran/spBFA")

Install by package version:
library("remotes")
install_version("spBFA", "1.3")



Attach the package and use:
library("spBFA")
Maintained by
Samuel I. Berchuck
[Scholar Profile | Author Map]
First Published: 2019-10-30
Latest Update: 2023-03-21
Description:
Implements a spatial Bayesian non-parametric factor analysis model with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC). Spatial correlation is introduced in the columns of the factor loadings matrix using a Bayesian non-parametric prior, the probit stick-breaking process. Areal spatial data is modeled using a conditional autoregressive (CAR) prior and point-referenced spatial data is treated using a Gaussian process. The response variable can be modeled as Gaussian, probit, Tobit, or Binomial (using Polya-Gamma augmentation). Temporal correlation is introduced for the latent factors through a hierarchical structure and can be specified as exponential or first-order autoregressive. Full details of the package can be found in the accompanying vignette. Furthermore, the details of the package can be found in "Bayesian Non-Parametric Factor Analysis for Longitudinal Spatial Surfaces", by Berchuck et al (2019), <doi:10.48550/arXiv.1911.04337>. The paper is in press at the journal Bayesian Analysis.
How to cite:
Samuel I. Berchuck (2019). spBFA: Spatial Bayesian Factor Analysis. R package version 1.3, https://cran.r-project.org/web/packages/spBFA. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0 (2019-10-30 18:00), 1.1 (2021-04-27 09:30), 1.2 (2022-09-04 19:40)
Other packages that cited spBFA R package
View spBFA citation profile
Other R packages that spBFA depends, imports, suggests or enhances
Complete documentation for spBFA
Functions, R codes and Examples using the spBFA R package
Some associated functions: bfa_sp . diagnostics . is.spBFA . predict.spBFA . reg.bfa_sp . spBFA . 
Some associated R codes: DIAG_diagnostics.R . MCMC_CheckInputs.R . MCMC_Create.R . MCMC_Utilities.R . MCMC_bfa_sp.R . PRED_predict.R . RcppExports.R . reg.bfa_sp-data.R . spBFA-package.R .  Full spBFA package functions and examples
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