Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS) — ##plugins.generic.mcfnsReadingTools.readingTools##

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COMPARING PROPERTIES OF SELF-REFERENCING MODELS BASED ON NONLINEAR-FIXED-EFFECTS VERSUS NONLINEAR-MIXED-EFFECTS MODELING APPROACHES

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1.Title##plugins.generic.mcfnsReadingTools.titleLabel##COMPARING PROPERTIES OF SELF-REFERENCING MODELS BASED ON NONLINEAR-FIXED-EFFECTS VERSUS NONLINEAR-MIXED-EFFECTS MODELING APPROACHES
2.Creator##plugins.generic.mcfnsReadingTools.creators##Chris J. Cieszewski; The University of Georgia, USA; Stati Uniti
2.Creator##plugins.generic.mcfnsReadingTools.creators##Mike Strub; University of Georgia, Athens, GA, USA; Stati Uniti
3.Subject##plugins.generic.mcfnsReadingTools.keywords##Mixed-Effects; Fixed-Effects; Self-Referencing; Base-Age-Invariance; Path-Invariance; Invariance Under Reparameterization; Well-Behaved Models; Model Conditioning; Site Models
3.Subject##plugins.generic.mcfnsReadingTools.disciplines##Growth and Yield; Inventory; Biometrics
4.Description##plugins.generic.mcfnsReadingTools.abstract##In this study, we compare the properties of self-referencing models, such as various site dependent growth and yield models for predictions of height, diameter, basal area, volume, and density, developed using Nonlinear-Fixed-Effects (NFE) versus Nonlinear-Mixed-Effects (NME) modeling approaches. The properties investigated include the following core traditional well-behaved model characteristics applicable to self-referencing functions: Base-Age-Invariance, Path-Invariance, Indifference Under Model Reparameterization, and Model Conditioning to have the predictions at the base-age equal to the reference point, as well as estimation and prediction statistics such as bias and variance of the fitted versus predicted residuals. The results of this investigation demonstrate that self-referencing models based on the NFE approach possess all the desirable properties associated with logical behavior of the model and estimation statistics, while the NME based self-referencing models lack the well-behaved model properties. We illustrate these properties using an example of fitting self-referencing models to panel data of loblolly pine age-height measurements on a range of sites from the South Africa Correlated Curve Trend Study.
5.Publisher##plugins.generic.mcfnsReadingTools.publisher##Contemporary Journal Concept Press
6.Contributor##plugins.generic.mcfnsReadingTools.contributors##University of Georgia
7.Date##plugins.generic.mcfnsReadingTools.date##2018-10-30
8.Type##plugins.generic.mcfnsReadingTools.type##Text.Serial.Journal; Mixed Effects Models, Fixed Effects Models
9.Format##plugins.generic.mcfnsReadingTools.format##PDF (inglese); application/pdf
10.Identifier##plugins.generic.mcfnsReadingTools.identifier##https://mcfns.com/index.php/Journal/it/article/view/10.11
11.Source##plugins.generic.mcfnsReadingTools.source##Mathematical and Computational Forestry & Natural-Resource Sciences (MCFNS); V. 10 N. 2: MCFNS October 30, 2018; 46-57 (12)
11.Source##plugins.generic.mcfnsReadingTools.onlineIssn##1946-7664
12.Language##plugins.generic.mcfnsReadingTools.language##en
13.Relation##plugins.generic.mcfnsReadingTools.suppFiles##
14.Coverage##plugins.generic.mcfnsReadingTools.coverageGeo##
15.Rights##plugins.generic.mcfnsReadingTools.rights##2018