Markov and semi-Markov switching linear mixed models used to identify forest tree growth components

Biometrics

Volumn 66, Issue 3, 2010, Pages 753-762

  Chaubert Pereira, Florence ^a   Guédon, Yann ^a   Lavergne, Christian ^b   Trottier, Catherine ^b  

^a CIRAD   (France)

^b UNIVERSITÉ PAUL VALÉRY   (France)

Author keywords

Individual random effect; Markov switching model; MCEM algorithm; Plant structure analysis; Semi Markov switching model

Indexed keywords

FORESTRY; IMAGE SEGMENTATION; MARKOV PROCESSES; MAXIMUM PRINCIPLE;

INDIVIDUAL RANDOM EFFECT; LINEAR MIXED MODELS; MARKOV SWITCHING; MARKOV SWITCHING MODELS; MCEM ALGORITHM; PLANT STRUCTURE ANALYSIS; RANDOM EFFECTS; SEMI-MARKOV; SEMI-MARKOV SWITCHING MODEL;

CHAINS;

ALGORITHM; CLIMATE EFFECT; CONIFEROUS TREE; COVARIANCE ANALYSIS; GROWTH MODELING; GROWTH RATE; HETEROGENEITY; MARKOV CHAIN; MONTE CARLO ANALYSIS; NUMERICAL MODEL; SAMPLING; SHOOT;

EID: 77956852086     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2009.01338.x     Document Type: Article

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