Optimal designs when the variance is a function of the mean.

Abstract:

:We develop locally D-optimal designs for nonlinear models when the variance of the response is a function of its mean. Using the two-parameter Michaelis-Menten model as an example, we show that the optimal design depends on both the type of heteroscedasticity and the magnitude of the variation. In addition, our results suggest that the homoscedastic D-optimal design has high efficiency under a broad class of heteroscedastic patterns and that it is fairly insensitive to nominal values of the parameters.

journal_name

Biometrics

journal_title

Biometrics

authors

Dette H,Wong WK

doi

10.1111/j.0006-341x.1999.00925.x

subject

Has Abstract

pub_date

1999-09-01 00:00:00

pages

925-9

issue

3

eissn

0006-341X

issn

1541-0420

journal_volume

55

pub_type

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