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D-Optimal Designs for Exponential and Poisson Regression Models

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Title D-Optimal Designs for Exponential and Poisson Regression Models
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Creator Shwetank Lall
Seema Jaggi
Eldho Varghese
Cini Varghese
Arpan Bhowmik
 
Subject Candidate set
D-optimality
Fisher information matrix
General equivalence theorem
Modified Fedorov exchange algorithm
Standardized variance function
 
Description Not Available
In the present study, the class of nonlinear models, with intrinsically linearly related mean response and input variables, were explored for the
generation of locally D-optimal designs. It has been found that these models have the advantage of design construction in transformed or coded design
space with suitable transformation in initial parameter guesses. Exponential and Poisson regression models with two continuous input variables were
investigated. For the construction of D-optimal designs, the modified version of Fedorov algorithm was used that require a suitable candidate set
representing the design space along with the initial parameter guesses. The efficient method of constructing the candidate sets with respect to each
model is proposed. The optimality of generated designs was validated using general equivalence theorem.
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Date 2018-05-04T10:18:59Z
2018-05-04T10:18:59Z
2018-04
 
Type Research Paper
 
Identifier Lall, S., Jaggi, S., Varghese, E., Varghese, C. and Bhowmik, A. (2018). D-Optimal Designs for Exponential and Poisson Regression Models. Journal of the Indian Society of Agricultural Statistics, 72(1), 27-32.
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http://krishi.icar.gov.in/jspui/handle/123456789/6053
 
Language English
 
Relation Not Available;
 
Publisher Journal of Indian Society of Agricultural Statistics