Szajowski, Krzysztof (2008): On a random number of disorders. Forthcoming in: Probability and Mathematical Statistics : pp. 134.

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Abstract
We register a random sequence which has the following properties: it has three segments being the homogeneous Markov processes. Each segment has his own one step transition probability law and the length of the segment is unknown and random. It means that at two random successive moments (they can be equal also and equal zero too) the source of observations is changed and the first observation in new segment is chosen according to new transition probability starting from the last state of the previous segment. In effect the number of homogeneous segments is random. The transition probabilities of each process are known and a priori distribution of the disorder moments is given. The former research on such problem has been devoted to various questions concerning the distribution changes. The random number of distributional segments creates new problems in solutions with relation to analysis of the model with deterministic number of segments. Two cases are presented in details. In the first one the objectives is to stop on or between the disorder moments while in the second one our objective is to find the strategy which immediately detects the distribution changes. Both problems are reformulated to optimal stopping of the observed sequences. The detailed analysis of the problem is presented to show the form of optimal decision function.
Item Type:  MPRA Paper 

Original Title:  On a random number of disorders 
English Title:  On a Random Number of Disorders 
Language:  English 
Keywords:  disorder problem, sequential detection, optimal stopping, Markov process, change point, double optimal stopping 
Subjects:  C  Mathematical and Quantitative Methods > C0  General > C02  Mathematical Methods C  Mathematical and Quantitative Methods > C6  Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61  Optimization Techniques ; Programming Models ; Dynamic Analysis C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C11  Bayesian Analysis: General 
Item ID:  20256 
Depositing User:  Krzysztof Szajowski 
Date Deposited:  27. Jan 2010 16:21 
Last Modified:  18. Feb 2013 20:45 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/20256 