Bayesian Ds-optimal designs for generalized linear models with varying dispersion parameter
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作者:
Pinto, Edmilson Rodrigues
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Univ Fed Uberlandia, Dept Math, Av Joao Naves Avila 2121, BR-38400 Uberlandia, MG, BrazilUniv Fed Uberlandia, Dept Math, Av Joao Naves Avila 2121, BR-38400 Uberlandia, MG, Brazil
Pinto, Edmilson Rodrigues
[1
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de Leon, Antonio Ponce
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Univ Estado Rio De Janeiro, Inst Social Med, Dept Epidemiol, BR-20550 Rio De Janeiro, BrazilUniv Fed Uberlandia, Dept Math, Av Joao Naves Avila 2121, BR-38400 Uberlandia, MG, Brazil
de Leon, Antonio Ponce
[2
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机构:
[1] Univ Fed Uberlandia, Dept Math, Av Joao Naves Avila 2121, BR-38400 Uberlandia, MG, Brazil
[2] Univ Estado Rio De Janeiro, Inst Social Med, Dept Epidemiol, BR-20550 Rio De Janeiro, Brazil
In this article we extend the theory of optimum designs for generalized linear models, addressing the optimality of designs for parameter estimation in a location-dispersion model when either not all p parameters in the mean model or not all q parameters in the dispersion model are of interest. The criterion of Bayesian D-s-optimality is adopted and its properties are derived. The theory is illustrated with an example from the coffee industry.
机构:
Univ Calif Santa Barbara, Dept Mech & Environm Engn, Santa Barbara, CA 93106 USAUniv Calif Santa Barbara, Dept Mech & Environm Engn, Santa Barbara, CA 93106 USA
Bamieh, B
Giarré, L
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机构:Univ Calif Santa Barbara, Dept Mech & Environm Engn, Santa Barbara, CA 93106 USA
机构:
Peking Univ, Ctr Stat Sci, Sch Math Sciences, LMAM, Beijing, Beijing, Peoples R ChinaPeking Univ, Ctr Stat Sci, Sch Math Sciences, LMAM, Beijing, Beijing, Peoples R China
Huang, Yimin
Kong, Xiangshun
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Beijing Inst Technol, Sch Math, Stat, Beijing, Beijing, Peoples R ChinaPeking Univ, Ctr Stat Sci, Sch Math Sciences, LMAM, Beijing, Beijing, Peoples R China
Kong, Xiangshun
Ai, Mingyao
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Peking Univ, Ctr Stat Sci, Sch Math Sciences, LMAM, Beijing, Beijing, Peoples R ChinaPeking Univ, Ctr Stat Sci, Sch Math Sciences, LMAM, Beijing, Beijing, Peoples R China