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Title: Statistical Inference about the Drift Parameter in Stochastic Processes (English)
Author: Stibůrek, David
Language: English
Journal: Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
ISSN: 0231-9721
Volume: 52
Issue: 2
Year: 2013
Pages: 107-120
Summary lang: English
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Category: math
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Summary: In statistical inference on the drift parameter $a$ in the Wiener process with a constant drift $Y_{t} = at+W_{t}$ there is a large number of options how to do it. We may, for example, base this inference on the properties of the standard normal distribution applied to the differences between the observed values of the process at discrete times. Although such methods are very simple, it turns out that more appropriate is to use the sequential methods. For the hypotheses testing about the drift parameter it is more proper to standardize the observed process, and to use the sequential methods based on the first time when the process reaches either $B$ or $-B$, where $B>0$, until some given time. These methods can be generalized to other processes, for instance, to the Brownian bridges. (English)
Keyword: Wiener process
Keyword: Brownian bridge
Keyword: symmetric process
Keyword: sequential methods
MSC: 60G15
MSC: 62F03
MSC: 62L10
idZBL: Zbl 06296019
idMR: MR3202384
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Date available: 2013-12-18T15:25:47Z
Last updated: 2014-07-30
Stable URL: http://hdl.handle.net/10338.dmlcz/143543
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