کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7547426 | 1489750 | 2016 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Hypothesis testing for Markovian models with random time observations
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
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چکیده انگلیسی
The aim of this paper is to propose a methodology for testing general hypotheses in a Markovian setting with random sampling. A discrete Markov chain X is observed at random time intervals Ïk, assumed to be i.i.d. with unknown distribution μ. Two test procedures are investigated. The first one is devoted to testing if the transition matrix P of the Markov chain X satisfies specific affine constraints, covering a wide range of situations such as symmetry or sparsity. The second procedure is a goodness-of-fit test on the distribution μ, which reveals to be consistent under mild assumptions even though the time gaps are not observed. The theoretical results are supported by a Monte Carlo simulation study to show the performance and robustness of the proposed methodologies on specific numerical examples.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 173, June 2016, Pages 87-98
Journal: Journal of Statistical Planning and Inference - Volume 173, June 2016, Pages 87-98
نویسندگان
Flavia Barsotti, Anne Philippe, Paul Rochet,