Title: Optimal designs for variance function estimation using sample variances
Authors: Goos, Peter ×
Tack, Lieven
Vandebroek, Martina #
Issue Date: Jan-2001
Publisher: Elsevier science bv
Series Title: Journal of statistical planning and inference vol:92 issue:1-2 pages:233-252
Abstract: Using sample variances for estimating a variance function is intuitively more appealing than using residuals. The main advantage of sample variances over residuals is that they do not require specification of a mean function. Based on maximum likelihood and weighted least squares estimation, two alternative approaches for the construction of optimal designs for variance function estimation with sample variances an proposed. Both methods are compared to existing approaches, A generic exchange algorithm and computational results are presented. Irrespective of the link function between the variance and the linear predictor, the algorithm serves as a useful tool to construct tailor-made designs for variance function estimation by means of sample variances. (C) 2001 Elsevier Science B.V. All rights reserved. MSG: 62K05; 62N10.
ISSN: 0378-3758
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
× corresponding author
# (joint) last author

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