Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10525478 | Journal of Statistical Planning and Inference | 2005 | 14 Pages |
Abstract
M-robust designs are defined and constructed for misspecified linear regression models with possibly autocorrelated errors on a discrete design space. These designs minimize the mean-squared errors if linear regression models are correct with uncorrelated errors, subject to two robust constraints which control the change of the bias and the change of variance under model departures. Simulated annealing algorithm is applied to construct M-robust designs. Examples are given to show M-robust designs and compare them with minimax robust designs.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Yu-Ling Tsai, Julie Zhou,