(Q104594999)

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Dynamic spatial regression models for space-varying forest stand tables

scientific article published in December 2014

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Dynamic spatial regression models for space-varying forest stand tables (English)

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Sudipto Banerjee

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Andrew O. Finley

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Aaron R. Weiskittel

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Chad Babcock

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Bruce D. Cook

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publication date

December 2014

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published in

Environmetrics

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25

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issue

8

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page(s)

596-609

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Predictive model assessment for count data

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Inference from Iterative Simulation Using Multiple Sequences

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Assessing the Feasibility of Low-Density LiDAR for Stand Inventory Attribute Predictions in Complex and Managed Forests of Northern Maine, USA

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Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America

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Hierarchical factor models for large spatially misaligned data: a low-rank predictive process approach

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Preserving correlation while modelling diameter distributions

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Modelling tree diameter from airborne laser scanning derived variables: A comparison of spatial statistical models

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7 January 2021

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Bayesian measures of model complexity and fit

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https://api.crossref.org/works/10.1002%2FENV.2322

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7 January 2021

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Forest Growth and Yield Modeling

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10.1002/ENV.2322

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(Q104594999)

Dynamic spatial regression models for space-varying forest stand tables

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