Recognizing van Deusen’s mixed estimator for annual forest inventory as a linear mixed model

David L.R. Affleck; George C. Gaines

doi:10.1139/cjfr-2024-0180

Treesearch

Recognizing van Deusen’s mixed estimator for annual forest inventory as a linear mixed model

Formally Refereed

Authors:

David L.R. Affleck, George C. Gaines

Year:

2025

Type:

Scientific Journal

Station:

Rocky Mountain Research Station

DOI:

https://doi.org/10.1139/cjfr-2024-0180

Source:

Canadian Journal of Forest Research. 55: 1-10.

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Abstract

The mixed estimator (ME) for annual forest inventory proposed by van Deusen (1999; Can. J. For. Res. 29: 1824-1828) is reformulated as a linear mixed model. This equivalent structure admits an interpretation of the ME as a polynomial regression on year with correlated year-specific random effects. It also uncovers the necessary criterion for maximum likelihood (ML) estimation. The improved performance of the ME under ML estimation is illustrated through simulations and application to inventory data from Montana, USA. Limitations of the ME relating to model-misspecification are also discussed.

Keywords

forest inventory, mixed models, penalized estimation, small area estimaton, Fay-Herriot models

Citation

Affleck, David L.R.; Gaines, George C., III. 2025. Recognizing van Deusen’s mixed estimator for annual forest inventory as a linear mixed model. Canadian Journal of Forest Research. 55: 1-10.