Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit-Reference-Cited by-同舟云学术

Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit

Published:2019-08-23 Issue:2 Volume:40 Page:352-369
ISSN:0272-4332
Container-title:Risk Analysis
language:en
Short-container-title:Risk Analysis

Author:

Schmidt Philip J.¹,Emelko Monica B.¹,Thompson Mary E.²

Affiliation:

1. Department of Civil & Environmental EngineeringUniversity of Waterloo Waterloo Ontario Canada

2. Department of Statistics & Actuarial ScienceUniversity of Waterloo Waterloo Ontario Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Alberta Innovates

Publisher

Wiley

Subject

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

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.13386

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3. Learning something from nothing: The critical importance of rethinking microbial non‐detects;Chik A. H.;Frontiers in Microbiology,2018

4. Estimation of Bacterial Densities by Means of the "Most Probable Number"

5. Determining the parametric structure of models

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