Matrix Models
- By Carlos Polanco1
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View Affiliations Hide AffiliationsAffiliations: 1 Department of Electromechanical Instrumentation, Instituto Nacional de Cardiología Ignacio Chávez, México | Faculty of Sciences, Universidad Nacional Autónoma de México, México
- Source: Markov Chain Process: Theory and Cases , pp 8-21
- Publication Date: June 2023
- Language: English
This chapter describes and provides an example of the matrix models: Lefkovitch model, Leslie model, Malthus model, and stability matrix models. From these the Discrete- and Continuous-Time Markov Chain Process is introduced. These matrix models are presented as they were historically occurring, and it is highlighted how the matrix structure offers a simple algebraic solution to problems involving multiple variables, where the elements of those matrices are conditional probabilities when going from a state A (row i) to a state B (column j). Once these matrix models have been defined and exemplified, it is shown that the eigenval ues and eigenvectors of the conditional probability matrix determine the long-term stability matrix of the Markov Chain Process.
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