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Inventory Control Under Parametric Uncertainty of Underlying Models Read chapter Read first chapter

2013 | OriginalPaper | Chapter

The Further Development of Stem Taper and Volume Models Defined by Stochastic Differential Equations

Author : Petras Rupšys

Published in: IAENG Transactions on Engineering Technologies

Publisher: Springer Netherlands

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Abstract

Stem taper process measured repeatedly among a series of individual trees is standardly analyzed by fixed and mixed regression models. This stem taper process can be adequately modeled by parametric stochastic differential equations (SDEs). We focus on the segmented stem taper model defined by the Gompertz, geometric Brownian motion and Ornstein-Uhlenbeck stochastic processes. This class of models enables the representation of randomness in the taper dynamics. The parameter estimators are evaluated by maximum likelihood procedure. The SDEs stem taper models were fitted to a data set of Scots pine trees collected across the entire Lithuanian territory. Comparison of the predicted stem taper and stem volume with those obtained using regression based models showed a predictive power to the SDEs models.

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previous chapter Least Squares Data Fitting Subject to Decreasing Marginal Returns
next chapter Computing Compressible Two-Component Flow Systems Using Diffuse Interface Method
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Metadata
Title
The Further Development of Stem Taper and Volume Models Defined by Stochastic Differential Equations
Author
Petras Rupšys
Copyright Year
2013
Publisher
Springer Netherlands
Book
IAENG Transactions on Engineering Technologies

Print ISBN: 978-94-007-6189-6

Electronic ISBN: 978-94-007-6190-2

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-94-007-6190-2_10