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Journal of Quantitative Economics

Erschienen in:

23.05.2022 | Original Article

Locally D-Optimal Designs for Binary Responses and Multiple Continuous Design Variables

verfasst von: Zhongshen Wang, John Stufken

Erschienen in: Journal of Quantitative Economics | Sonderheft 1/2022

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Abstract

We identify locally D-optimal designs for binary data when a generalized linear model with multiple continuous covariates whose values can be selected at the design stage. Yang et al. (Stat Sin 21:1415–1430, 2011) provided an explicit form for D-optimal designs when there are no interaction effects between the design variables. After providing an alternative proof of that result, we generalize the result by identifying D-optimal designs for models with interactions between the design variables that satisfy the strong effect heredity principle. We also employ orthogonal arrays to obtain more practical D-optimal designs with a smaller support size.

Vorheriger Artikel Reverse Regressions, Symmetry and Test Distributions in Linear Models

Nächster Artikel Factor Analysis Regression for Predictive Modeling with High-Dimensional Data

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Titel: Locally D-Optimal Designs for Binary Responses and Multiple Continuous Design Variables
verfasst von: Zhongshen Wang
John Stufken
Publikationsdatum: 23.05.2022
Verlag: Springer India
Erschienen in: Journal of Quantitative Economics / Ausgabe Sonderheft 1/2022
Print ISSN: 0971-1554
Elektronische ISSN: 2364-1045
DOI: https://doi.org/10.1007/s40953-022-00304-z

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