Modelling and forecasting vehicle stocks using the trends of stochastic Gompertz diffusion models: The case of Spain
In the present study, we treat the stochastic homogeneous Gompertz diffusion process (SHGDP) by the approach of the Kolmogorov equation. Firstly, using a transformation in diffusion processes, we show that the probability transition density function of this process has a lognormal time‐dependent dis...
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Published in | Applied stochastic models in business and industry Vol. 25; no. 3; pp. 385 - 405 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
01.05.2009
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Subjects | |
Online Access | Get full text |
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Summary: | In the present study, we treat the stochastic homogeneous Gompertz diffusion process (SHGDP) by the approach of the Kolmogorov equation. Firstly, using a transformation in diffusion processes, we show that the probability transition density function of this process has a lognormal time‐dependent distribution, from which the trend and conditional trend functions and the stationary distribution are obtained. Second, the maximum likelihood approach is adapted to the problem of parameters estimation in the drift and the diffusion coefficient using discrete sampling of the process, then the approximated asymptotic confidence intervals of the parameter are obtained. Later, we obtain the corresponding inference of the stochastic homogeneous lognormal diffusion process as limit from the inference of SHGDP when the deceleration factor tends to zero. A statistical methodology, based on the above results, is proposed for trend analysis. Such a methodology is applied to modelling and forecasting vehicle stocks. Finally, an application is given to illustrate the methodology presented using real data, concretely the total vehicle stocks in Spain. Copyright © 2008 John Wiley & Sons, Ltd. |
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Bibliography: | istex:7A8F50355779B8AF7E9C12EA8033091E7913F509 ArticleID:ASMB754 Junta de Andalucía - No. P06-FQM-02271 Ministerio de Educación y Ciencia - No. MTM 2005-09209; No. MTM-2008-05785 ark:/67375/WNG-QX3ZDJGC-P ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 1524-1904 1526-4025 |
DOI: | 10.1002/asmb.754 |