Are Nonprofit Antipoverty Organizations Located Where They Are Needed? A Spatial Analysis of the Greater Hartford Region

DOI10.1080/00031305.2014.955211OpenAlexW2123368307WikidataQ58251087 ScholiaQ58251087MaRDI QIDQ5877677

Chao Guo, Jun Yan, Laurie E. Paarlberg

Publication date: 15 February 2023

Published in: The American Statistician (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00031305.2014.955211

zbMATH Keywords

zero-inflated Poissonspatial random effectintrinsic conditional autoregressive

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• CODA
• boa
• BUGS

Cites Work

• Unnamed Item
• Unnamed Item
• Bayesian image restoration, with two applications in spatial statistics (with discussion)
• Inference from iterative simulation using multiple sequences
• Bayesian analysis of zero-inflated regression models
• On the Precision of the Conditionally Autoregressive Prior in Spatial Models
• Sampling-Based Approaches to Calculating Marginal Densities
• Penalized loss functions for Bayesian model comparison
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• A Predictive Approach to Model Selection
• A spatial scan statistic
• Bayesian Approach for Nonlinear Random Effects Models
• Bayesian Measures of Model Complexity and Fit
• Bayes Factors
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
• Deviance information criteria for missing data models

This page was built for publication: Are Nonprofit Antipoverty Organizations Located Where They Are Needed? A Spatial Analysis of the Greater Hartford Region