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Consistency Properties for Growth Model Parameters Under an Infill Asymptotics Domain

Consistency Properties for Growth Model Parameters Under an Infill Asymptotics Domain

Paperback

General ScienceProbability & Statistics

ISBN10: 1025123646
ISBN13: 9781025123646
Publisher: Hutson Street Press
Published: May 22 2025
Pages: 94
Weight: 0.32
Height: 0.19 Width: 6.14 Depth: 9.21
Language: English

Growth curves are used to model various processes, and are often seen in biological and agricultural studies. Underlying assumptions of many studies are that the process may be sampled forever, and that samples are statistically independent. We instead consider the case where sampling occurs in a finite domain, so that increased sampling forces samples closer together, and also assume a distance-based covariance function. We first prove that, under certain conditions, the mean parameter of a fixed-mean model cannot be estimated within a finite domain. We then numerically consider more complex growth curves, examining sample sizes, sample spacing, and quality of parameter estimates, and close with recommendations to practitioners.

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