Optimal designs for binary response models with multiple nonnegative variables

Shih Hao Huang; Mong Na Lo Huang; Cheng Wei Lin

doi:10.1016/j.jspi.2019.09.006

Optimal designs for binary response models with multiple nonnegative variables

Shih Hao Huang, Mong Na Lo Huang, Cheng Wei Lin

數學系

研究成果: 雜誌貢獻 › 期刊論文 › 同行評審

1 引文斯高帕斯（Scopus）

摘要

In this work we investigate locally optimal designs for binary response models with multiple nonnegative explanatory variables. We characterize an essentially complete class with respect to Schur ordering, in which a scaled ϕ_p-optimal design exists for any given p∈[−∞,1]. In particular, we explicitly identify D-optimal designs for logit, probit, double exponential, double reciprocal models within the class.

原文	???core.languages.en_GB???
頁（從 - 到）	75-83
頁數	9
期刊	Journal of Statistical Planning and Inference
卷	206
DOIs	https://doi.org/10.1016/j.jspi.2019.09.006
出版狀態	已出版 - 5月 2020

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10.1016/j.jspi.2019.09.006

應用於影像資料之信息式典型分析(2/2)
Huang, S.-H. (PI)
1/08/19 → 31/10/20
研究計畫: Research

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abstract = "In this work we investigate locally optimal designs for binary response models with multiple nonnegative explanatory variables. We characterize an essentially complete class with respect to Schur ordering, in which a scaled ϕp-optimal design exists for any given p∈[−∞,1]. In particular, we explicitly identify D-optimal designs for logit, probit, double exponential, double reciprocal models within the class.",

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AB - In this work we investigate locally optimal designs for binary response models with multiple nonnegative explanatory variables. We characterize an essentially complete class with respect to Schur ordering, in which a scaled ϕp-optimal design exists for any given p∈[−∞,1]. In particular, we explicitly identify D-optimal designs for logit, probit, double exponential, double reciprocal models within the class.

KW - D-optimality

KW - Essentially complete class

KW - Scaled ϕ-optimality

KW - Schur ordering

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Optimal designs for binary response models with multiple nonnegative variables

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應用於影像資料之信息式典型分析(2/2)

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