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- Title
THE USE OF SIMPLIFIED OR MISSPECIFIED MODELS: LINEAR CASE.
- Authors
Shaohua Wu; Harris, T. J.; McAuley, K. B.
- Abstract
Simplified models have many appealing properties and sometimes give better parameter estimates and model predictions, in sense of mean-squared-error, than extended models, especially when the data are not informative. In this paper, we summarize extensive quantitative and qualitative results in the literature concerned with using simplified or misspecified models. Based on confidence intervals and hypothesis tests, we develop a practical strategy to help modellers decide whether a simplified model should be used, and point out the difficulty in making such a decision. We also evaluate several methods for statistical inference for simplified or misspecified models.
- Subjects
HYPOTHESIS; STATISTICAL hypothesis testing; DECISION making; REASONING; STATISTICAL sampling; CONFIDENCE intervals
- Publication
Canadian Journal of Chemical Engineering, 2007, Vol 85, Issue 4, p386
- ISSN
0008-4034
- Publication type
Article
- DOI
10.1002/cjce.5450850401