Model Selection and Estimation with Quantal‐Response Data in Benchmark Risk Assessment-Reference-Cited by-同舟云学术

Model Selection and Estimation with Quantal‐Response Data in Benchmark Risk Assessment

Published:2016-06-20 Issue:4 Volume:37 Page:716-732
ISSN:0272-4332
Container-title:Risk Analysis
language:en
Short-container-title:Risk Analysis

Author:

Peña Edsel A.¹,Wu Wensong²,Piegorsch Walter³,West Ronald W.⁴,An LingLing⁵

Affiliation:

1. Department of Statistics University of South Carolina Columbia SC USA

2. Department of Mathematics and Statistics Florida International University Miami FL USA

3. Program in Statistics and BIO5 Institute University of Arizona Tucson AZ USA

4. Department of Statistics North Carolina State University Raleigh NC USA

5. Program of Statistics, Department of Agricultural and Biosystems Engineering University of Arizona Tucson AZ USA

Funder

National Science Foundation

National Institutes of Health

Publisher

Wiley

Subject

Physiology (medical),Safety, Risk, Reliability and Quality

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.12644

Reference38 articles.

1. AkaikeH.Information theory and an extension of the maximum likelihood principle. Pp. 267–281 in Second International Symposium on Information Theory (Tsahkadsor 1971) Budapest: Akadémiai Kiadó 1973.

2. Model Uncertainty and Risk Estimation for Experimental Studies of Quantal Responses

3. Confidence limits on one-stage model parameters in benchmark risk assessment

4. A large-sample model selection criterion based on Kullback's symmetric divergence

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