The Batch Markovian Arrival Process Subject to Renewal Generated Geometric Catastrophes
Antonis Economou, A. Gómez‐Corral
Abstract
Antonis Economou, A. Gómez‐Corral
Abstract
We deal with a population of individuals that grows stochastically according to a batch Markovian arrival process and is subject to renewal generated geometric catastrophes. Our interest is in the semi-regenerative process that describes the population size at arbitrary times. The main feature of the underlying Markov renewal process is the block structure of its embedded Markov chain. Specifically, the embedded Markov chain at post-catastrophe epochs may be thought of as a Markov chain of GI/G/1-type, which is indeed amenable to be studied through its R- and G-measures, and a suitably defined Markov chain of M/G/1-type. We present tractable formulae for a variety of probabilistic descriptors of the population, including the equilibrium distribution of the population size and the distribution of the time to extinction for present units at post-catastrophe epochs.
OpenAlex reports 25 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
We deal with a population of individuals that grows stochastically according to a batch Markovian arrival process and is subject to renewal generated geometric catastrophes. Our interest is in the semi-regenerative process that describes the population size at arbitrary times. The main feature of the underlying Markov renewal process is the block structure of its embedded Markov chain. Specifically, the embedded Markov chain at post-catastrophe epochs may be thought of as a Markov chain of GI/G/1-type, which is indeed amenable to be studied through its R- and G-measures, and a suitably defined Markov chain of M/G/1-type. We present tractable formulae for a variety of probabilistic descriptors of the population, including the equilibrium distribution of the population size and the distribution of the time to extinction for present units at post-catastrophe epochs.
Key concepts: Markovian arrival process, Mathematics, Renewal theory, Markov process, Process (computing), Subject (documents), Statistical physics, Stochastic process