Overcoming data sparseness and parametric constraints in modeling of tree mortality: A new nonparametric Bayesian model

Canadian Journal of Forest Research

Volumn 39, Issue 9, 2009, Pages 1677-1687

  Metcalf, C Jessica E ^a,e   McMahon, Sean M ^b   Clark, James S ^b,c,d  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

^b SMITHSONIAN ENVIRONMENTAL RESEARCH CENTER   (United States)

^c DUKE UNIVERSITY   (United States)

^d Duke University   (United States)

^e PRINCETON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COVARIATES; DATA SPARSENESS; DIAMETER INCREMENT; ECOLOGICAL INFERENCES; FOREST DYNAMICS; MORTALITY MODEL; NON-PARAMETRIC BAYESIAN; NORTH CAROLINA , USA; PARAMETRIC CONSTRAINTS; SWEET GUM; TREE MORTALITY; TREE SPECIES;

FORESTRY;

BAYESIAN NETWORKS;

BAYESIAN ANALYSIS; COVARIANCE ANALYSIS; DECIDUOUS TREE; DIAMETER; ECOLOGICAL MODELING; FOREST MANAGEMENT; MORTALITY; TREEFALL;

ACER; DATA; ILEX; LIQUIDAMBAR; LIRIODENDRON; MATHEMATICAL MODELS; MORTALITY; TREES;

NORTH AMERICA; NORTH CAROLINA; UNITED STATES;

ACER; ILEX; LIQUIDAMBAR; LIQUIDAMBAR STYRACIFLUA; LIRIODENDRON; LIRIODENDRON TULIPIFERA; TULIPA;

EID: 70249120398     PISSN: 00455067     EISSN: None     Source Type: Journal    
DOI: 10.1139/X09-083     Document Type: Article

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