Optimal Design for Experiments with Potentially Failing Trials

We discuss the problem of optimal allocation of the design points of an experiment for the case where the trials may fail with non-zero probability. Numerical results for D-optimal designs are given for estimating the coefficients of a polynomial regression. For small sample sizes these designs may...

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Bibliographic Details
Main Author:	Hackl, Peter
Format:	Others
Language:	en
Published:	Department of Statistics and Mathematics, WU Vienna University of Economics and Business 1994
Subjects:	polynomial regression / failing trials / D-optimality
Online Access:	http://epub.wu.ac.at/68/1/document.pdf

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spelling	ndltd-VIENNA-oai-epub.wu-wien.ac.at-epub-wu-01_a232015-08-08T04:59:00Z Optimal Design for Experiments with Potentially Failing Trials Hackl, Peter polynomial regression / failing trials / D-optimality We discuss the problem of optimal allocation of the design points of an experiment for the case where the trials may fail with non-zero probability. Numerical results for D-optimal designs are given for estimating the coefficients of a polynomial regression. For small sample sizes these designs may deviate substantially from the corresponding designs in the case of certain response. They can be less efficient, but are less affected by failing trials. (author's abstract) Department of Statistics and Mathematics, WU Vienna University of Economics and Business 1994 Paper NonPeerReviewed en application/pdf http://epub.wu.ac.at/68/1/document.pdf Series: Forschungsberichte / Institut für Statistik http://epub.wu.ac.at/68/
collection	NDLTD
language	en
format	Others
sources	NDLTD
topic	polynomial regression / failing trials / D-optimality
spellingShingle	polynomial regression / failing trials / D-optimality Hackl, Peter Optimal Design for Experiments with Potentially Failing Trials
description	We discuss the problem of optimal allocation of the design points of an experiment for the case where the trials may fail with non-zero probability. Numerical results for D-optimal designs are given for estimating the coefficients of a polynomial regression. For small sample sizes these designs may deviate substantially from the corresponding designs in the case of certain response. They can be less efficient, but are less affected by failing trials. (author's abstract) === Series: Forschungsberichte / Institut für Statistik
author	Hackl, Peter
author_facet	Hackl, Peter
author_sort	Hackl, Peter
title	Optimal Design for Experiments with Potentially Failing Trials
title_short	Optimal Design for Experiments with Potentially Failing Trials
title_full	Optimal Design for Experiments with Potentially Failing Trials
title_fullStr	Optimal Design for Experiments with Potentially Failing Trials
title_full_unstemmed	Optimal Design for Experiments with Potentially Failing Trials
title_sort	optimal design for experiments with potentially failing trials
publisher	Department of Statistics and Mathematics, WU Vienna University of Economics and Business
publishDate	1994
url	http://epub.wu.ac.at/68/1/document.pdf
work_keys_str_mv	AT hacklpeter optimaldesignforexperimentswithpotentiallyfailingtrials
_version_	1716816270435811328

Optimal Design for Experiments with Potentially Failing Trials

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