Constructing Flexible, Identifiable and Interpretable Statistical Models for Binary Data-Reference-Cited by-同舟云学术

Constructing Flexible, Identifiable and Interpretable Statistical Models for Binary Data

Published:2022-01-30 Issue:2 Volume:90 Page:328-345
ISSN:0306-7734
Container-title:International Statistical Review
language:en
Short-container-title:Int Statistical Rev

Author:

Scharf Henry R.¹^ORCID,Lu Xinyi²,Williams Perry J.³,Hooten Mevin B.²⁴

Affiliation:

1. Department of Mathematics and Statistics San Diego State University San Diego CA USA

2. Department of Statistics Colorado State University Fort Collins CO USA

3. Department of Natural Resources and Environmental Science University of Nevada Reno NV USA

4. U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Department of Fish, Wildlife, and Conservation Biology Colorado State University Fort Collins CO USA

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/insr.12485

Reference58 articles.

1. Categorical Data Analysis

2. Bayesian Analysis of Binary and Polychotomous Response Data

3. An Autologistic Model for the Spatial Distribution of Wildlife

4. On the reliability of N-mixture models for count data

5. A Framework for Skew-Probit Links in Binary Regression

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