Non-Homogeneous Markov Set Systems

A more realistic way to describe a model is the use of intervals which contain the required values of the parameters. In practice we estimate the parameters from a set of data and it is natural that they will be in confidence intervals. In the present study, we study Non-Homogeneous Markov Systems (...

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Main Author: P.-C.G. Vassiliou
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/9/5/471
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author P.-C.G. Vassiliou
author_facet P.-C.G. Vassiliou
author_sort P.-C.G. Vassiliou
collection DOAJ
description A more realistic way to describe a model is the use of intervals which contain the required values of the parameters. In practice we estimate the parameters from a set of data and it is natural that they will be in confidence intervals. In the present study, we study Non-Homogeneous Markov Systems (NHMS) processes for which the required basic parameters are in intervals. We call such processes Non-Homogeneous Markov Set Systems (NHMSS). First we study the set of the relative expected population structure of memberships and we prove that under certain conditions of convexity of the intervals of the parameters the set is compact and convex. Next, we establish that if the NHMSS starts with two different initial distributions sets and allocation probability sets under certain conditions, asymptotically the two expected relative population structures coincide geometrically fast. We continue proving a series of theorems on the asymptotic behavior of the expected relative population structure of a NHMSS and the properties of their limit set. Finally, we present an application for geriatric and stroke patients in a hospital and through it we solve problems that surface in an application.
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spelling doaj.art-58d102118b9d40fda2856dd220ddada72023-12-11T18:23:39ZengMDPI AGMathematics2227-73902021-02-019547110.3390/math9050471Non-Homogeneous Markov Set SystemsP.-C.G. Vassiliou0Department of Statistical Science, University College London, Gower St, London WC1E 6BT, UKA more realistic way to describe a model is the use of intervals which contain the required values of the parameters. In practice we estimate the parameters from a set of data and it is natural that they will be in confidence intervals. In the present study, we study Non-Homogeneous Markov Systems (NHMS) processes for which the required basic parameters are in intervals. We call such processes Non-Homogeneous Markov Set Systems (NHMSS). First we study the set of the relative expected population structure of memberships and we prove that under certain conditions of convexity of the intervals of the parameters the set is compact and convex. Next, we establish that if the NHMSS starts with two different initial distributions sets and allocation probability sets under certain conditions, asymptotically the two expected relative population structures coincide geometrically fast. We continue proving a series of theorems on the asymptotic behavior of the expected relative population structure of a NHMSS and the properties of their limit set. Finally, we present an application for geriatric and stroke patients in a hospital and through it we solve problems that surface in an application.https://www.mdpi.com/2227-7390/9/5/471Non-Homogeneous Markov SystemsMarkov Set Systemslimiting set
spellingShingle P.-C.G. Vassiliou
Non-Homogeneous Markov Set Systems
Mathematics
Non-Homogeneous Markov Systems
Markov Set Systems
limiting set
title Non-Homogeneous Markov Set Systems
title_full Non-Homogeneous Markov Set Systems
title_fullStr Non-Homogeneous Markov Set Systems
title_full_unstemmed Non-Homogeneous Markov Set Systems
title_short Non-Homogeneous Markov Set Systems
title_sort non homogeneous markov set systems
topic Non-Homogeneous Markov Systems
Markov Set Systems
limiting set
url https://www.mdpi.com/2227-7390/9/5/471
work_keys_str_mv AT pcgvassiliou nonhomogeneousmarkovsetsystems