Distributional validation of precipitation data products with spatially varying mixture models
From MaRDI portal
Publication:6045985
DOI10.1007/s13253-022-00515-0OpenAlexW4296929565MaRDI QIDQ6045985
Philip A. White, Summer B. Rupper, Lynsie R. Warr, William F. Christensen, Matthew J. Heaton
Publication date: 15 May 2023
Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s13253-022-00515-0
Cites Work
- Unnamed Item
- Unnamed Item
- Markov chain Monte Carlo: can we trust the third significant figure?
- Data augmentation and parameter expansion for independent or spatially correlated ordinal data
- A clipped latent variable model for spatially correlated ordered categorical data
- Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
- Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
- Fixed Rank Kriging for Very Large Spatial Data Sets
- Gaussian Predictive Process Models for Large Spatial Data Sets
- Dealing With Label Switching in Mixture Models
- A Fused Gaussian Process Model for Very Large Spatial Data
- Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models
- Bayesian Analysis of Binary and Polychotomous Response Data
This page was built for publication: Distributional validation of precipitation data products with spatially varying mixture models
