Abstract
We investigate D-optimum designs for experiments in which a linear model holds after an unknown power transformation of the univariate response variable. This is a departure from standard D-optimal design in which an appropriate scale for the response is assumed known before data collection. The design problem that we formulate is intrinsically non-linear, requiring characterization of likely parameter values. Several applications are presented to illustrate the importance of recognizing the role of response transformations at the design stage.
Original language | English (US) |
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Pages (from-to) | 111-124 |
Number of pages | 14 |
Journal | Journal of the Royal Statistical Society. Series B: Statistical Methodology |
Volume | 59 |
Issue number | 1 |
DOIs | |
State | Published - 1997 |
Keywords
- Box-cox power transformations
- D-optimum designs
- D-optimum designs
- Heteroscedasticity
- Linear models