A New Class of Optimal Designs in the Presence of a Quantitative Covariate

No Thumbnail Available

Links to Files

https://csa.ru.ac.bd/stat-ijss/journals/v-14-iss-01/

Permanent Link

http://hdl.handle.net/11603/31683

Collections

UMBC Mathematics and Statistics Department
UMBC Faculty Collection

Author/Creator

Author/Creator ORCID

Date

2015-04-12

Type of Work

journal articles
Text

Department

Program

Citation of Original Publication

Sinha, Bikas K., et al. “A New Class of Optimal Designs in the Presence of a Quantitative Covariate.” International Journal of Statistical Sciences 14, 2014: 1-15. https://csa.ru.ac.bd/stat-ijss/journals/v-14-iss-01/.

Rights

This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

Treatment allocation experiments
models with covariates
optimal placement of covariate values
optimal allocations

Abstract

We propose to discuss at length the problem of placement of one controllable covariate in the context of an experiment involving several ‘treatments’. We do this while extracting maximum information on the unknown parameter attached to the covariate’s values in the mean model for the observations. The experimental set-up is a bit different, and this calls for an interesting non-trivial study on optimality in the context of a single-covariate linear regression model.