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- Petras Rupšys
- Journal of Forest Research
- 2014

Height–diameter modeling is most often performed using non-linear regression models based on ordinary differential equations. In this study, new models of tree height dynamics involving a stochastic differential equation and mixed-effects parameters are examined. We use a stochastic differential equation to describe the dynamics of the height of an… (More)

Height-diameter models are classically analyzed by fixed or mixed linear and non-linear regression models. In order to possess the among-plot variability, we propose stochastic differential equations that are deduced from the standard deterministic dynamic ordinary differential equations by adding the process variability to the growth dynamic. The advantage… (More)

- Petras Rupšys
- PloS one
- 2016

The aim of this paper is twofold: to introduce the mathematics of stochastic differential equations (SDEs) for forest dynamics modeling and to describe how such a model can be applied to aid our understanding of tree height distribution corresponding to a given diameter using the large dataset provided by the Lithuanian National Forest Inventory (LNFI).… (More)

- Edmundas Bartkevi, ius, Edmundas Petrauskas, Petras Rupšys, Graciano Russetti
- 2012

Abstract—An approach combining information generating from different stochastic differential equations are recognized for improving predictive quality of stem profile (taper). The stochastic differential equations stem taper models were fitted to a data set of Scots pine trees collected across the entire Lithuanian territory. Comparison of the predicted… (More)

- Petras Rupšys
- 2013

In this paper we use a stochastic differential equation to describe the dynamic evolution of the height of an individual tree. The first model is defined by Gompertz shape stochastic differential equation. The second model is defined by Gompertz stochastic differential equation with a threshold parameter. This model can be considered as an extension of the… (More)

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