spBFA

Spatial Bayesian Factor Analysis

CRAN Package

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.


Documentation


Team


Insights

Last 30 days

This package has been downloaded 165 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.

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0 downloadsMar 2, 2025
0 downloadsMar 3, 2025
8 downloadsMar 4, 2025
9 downloadsMar 5, 2025
5 downloadsMar 6, 2025
4 downloadsMar 7, 2025
6 downloadsMar 8, 2025
1 downloadsMar 9, 2025
4 downloadsMar 10, 2025
9 downloadsMar 11, 2025
1 downloadsMar 12, 2025
12 downloadsMar 13, 2025
3 downloadsMar 14, 2025
9 downloadsMar 15, 2025
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0 downloadsMar 17, 2025
11 downloadsMar 18, 2025
5 downloadsMar 19, 2025
8 downloadsMar 20, 2025
5 downloadsMar 21, 2025
12 downloadsMar 22, 2025
2 downloadsMar 23, 2025
9 downloadsMar 24, 2025
3 downloadsMar 25, 2025
2 downloadsMar 26, 2025
6 downloadsMar 27, 2025
13 downloadsMar 28, 2025
3 downloadsMar 29, 2025
4 downloadsMar 30, 2025
1 downloadsMar 31, 2025
4 downloadsApr 1, 2025
4 downloadsApr 2, 2025
0 downloadsApr 3, 2025
0 downloadsApr 4, 2025
0 downloadsApr 5, 2025
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The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 2,492 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 29 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


Binaries


Dependencies

  • Imports4 packages
  • Suggests5 packages
  • Linking To2 packages