CADENAS DE MARKOV EN TIEMPO DISCRETO PDF

E-mail: victor. Luis Calvo Mackenna. Antonio Varas In this paper we present a probabilistic model that contributes to the study of dynamics in the behavior and permanence of patients in a cardiovascular intensive care unit. The model corresponds to a discrete Markov Chain, that allows to predict the time that a patient remains in the system through the time, by means of certain severity of illness states and the corresponding transition probabilities between those states. The different states are based on the construction of a new score created for this study.

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We'd like to understand how you use our websites in order to improve them. Register your interest. In this article we present a generalization of Markov Decision Processes with discreet time where the immediate rewards in every period are not deterministic but random, with the two first moments of the distribution given.

Formulas are developed to calculate the expected value and the variance of the reward of the process, which formulas generalize and partially correct other results. We make some observations about the distribution of rewards for processes with limited or unlimited horizon and with or without discounting. Applications with risk sensitive policies are possible; this is illustrated in a numerical example where the results are revalidated by simulation.

This is a preview of subscription content, log in to check access. Brown, H. Martz Jr. Google Scholar. Download references. Reprints and Permissions. Benito, F. Calculating the variance in Markov-processes with random reward. Trabajos de Estadistica y de Investigacion Operativa 33, 73 Download citation. Search SpringerLink Search. Abstract In this article we present a generalization of Markov Decision Processes with discreet time where the immediate rewards in every period are not deterministic but random, with the two first moments of the distribution given.

References [1] D. You can also search for this author in PubMed Google Scholar. Rights and permissions Reprints and Permissions. About this article Cite this article Benito, F.

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Software educativo : cadenas de Markov en tiempo discreto

Important User Information: Remote access to EBSCO's databases is permitted to patrons of subscribing institutions accessing from remote locations for personal, non-commercial use. However, remote access to EBSCO's databases from non-subscribing institutions is not allowed if the purpose of the use is for commercial gain through cost reduction or avoidance for a non-subscribing institution. Abstract: In this paper we present a probabilistic model that contributes to the study of dynamics in the behavior and permanence of patients in a cardiovascular intensive care unit. The model corresponds to a discrete Markov Chain, that allows to predict the time that a patient remains in the system through the time, by means of certain severity of illness slates and the corresponding transition probabilities between those states.

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Calculating the variance in Markov-processes with random reward

Cadena markov definicin. Se tiene una cadena markov con dos estados nublado soleado. Modelo oculto markov. Desarrollo problema sobre cadenas markov.

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