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Title: The use of copulas to practical estimation of multivariate stochastic differential equation mixed effects models

A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.
Authors:
 [1]
  1. Aleksandras Stulginskis University, Studenų g. 11, Akademija, Kaunas district, LT – 53361 Lithuania (Lithuania)
Publication Date:
OSTI Identifier:
22492618
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1684; Journal Issue: 1; Conference: AMiTaNS'15: 7. international conference for promoting the application of mathematics in technical and natural sciences, Albena (Bulgaria), 28 Jun - 3 Jul 2015; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; BARK; COMPARATIVE EVALUATIONS; DENSITY FUNCTIONAL METHOD; DIFFERENTIAL EQUATIONS; DISTRIBUTION; FORECASTING; HEIGHT; LITHUANIA; M CODES; MAXIMUM-LIKELIHOOD FIT; MULTIVARIATE ANALYSIS; PINES; PROBABILITY DENSITY FUNCTIONS; STOCHASTIC PROCESSES