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Titlebook: Parameter Estimation in Stochastic Differential Equations; Jaya P. N. Bishwal Book 2008 Springer-Verlag Berlin Heidelberg 2008 Asymtotic T

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發(fā)表于 2025-3-21 19:21:00 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Parameter Estimation in Stochastic Differential Equations
編輯Jaya P. N. Bishwal
視頻videohttp://file.papertrans.cn/742/741136/741136.mp4
概述Includes supplementary material:
叢書(shū)名稱(chēng)Lecture Notes in Mathematics
圖書(shū)封面Titlebook: Parameter Estimation in Stochastic Differential Equations;  Jaya P. N. Bishwal Book 2008 Springer-Verlag Berlin Heidelberg 2008 Asymtotic T
描述.Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modelling complex phenomena and making beautiful decisions. The subject has attracted researchers from several areas of mathematics and other related fields like economics and finance. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods. Useful because of the current availability of high frequency data is the study of refined asymptotic properties of several estimators when the observation time length is large and the observation time interval is small. Also space time white noise driven models, useful for spatial data, and more sophisticated non-Markovian and non-semimartingale models like fractional diffusions that model the long memory phenomena are examined in this volume..
出版日期Book 2008
關(guān)鍵詞Asymtotic Theory; Diffusion Processes; Discrete Observations; Estimator; Martingale; Ornstein-Uhlenbeck p
版次1
doihttps://doi.org/10.1007/978-3-540-74448-1
isbn_softcover978-3-540-74447-4
isbn_ebook978-3-540-74448-1Series ISSN 0075-8434 Series E-ISSN 1617-9692
issn_series 0075-8434
copyrightSpringer-Verlag Berlin Heidelberg 2008
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Maximum Likelihood Estimation in Fractional Diffusionse solution of which is called fractional diffusion. The fBm being not a Markov process and not a semimartingale (except for the case where Hurst index is 1.2), the classical It? calculus is not applicable to develop its theory.
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Parametric Stochastic Differential Equations as errors of measurement (cf. Gelb (1974)). Other applications are in biology (cf. Jennrich and Bright (1976)), medicine (cf. Jones (1984)), econometrics (cf. Bergstrom (1976, 1988)), finance (cf. Black and Scholes (1973)), geophysics (cf. Arato (1982)) and oceanography (cf. Adler . (1996)).
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n die Grundkonzepte und -theorien der Logistik erl?utert. Die Erkl?rungen sind kompakt und verst?ndlich formuliert und bieten somit Basiswissen für alle, die einen schnellen Einstieg in die Praxis suchen, sich für Logistik und Beschaffung interessieren oder ihr vorhandenes Wissen auffrischen m?chten.
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