spBFA
1.5.0Spatial Bayesian Factor Analysis
Overview
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:10.1214/20-BA1253 in Bayesian Analysis.
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- Return-value docs
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- References docs
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6 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2026-01-22issues were not corrected in time
- 1.5.02026-01-07 · diff ↗
- 1.4.02025-09-30 · diff ↗
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.32023-03-21 · diff ↗
- 1.22022-09-04 · diff ↗
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.12021-04-27 · diff ↗
- unarchivedReturned to CRAN2021-04-27
- archivedRemoved from CRAN2021-04-21check problems were not corrected in time
- RR 4.0.0 released · 2020-04-24
- 1.02019-10-30
Show 1 earlier events
- RR 3.6.0 released · 2019-04-26
Package metadata
- Total releases
- 6
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.0.2
- Bundled data
- 2.3 MB / 1 file
- Download size
- not tracked yet
- Installed size
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- With dependencies
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