AbstractWe consider convergence of Markov chains with uncertain parameters, known as imprecise Markov chains, which contain an absorbing state. We prove that under conditioning on non-absorption the imprecise conditional probabilities converge independently of the initial imprecise probability distribution if some regularity conditions are assumed. This is a generalisation of a known result from the classical theory of Markov chains by Darroch and Seneta [6]
Imprecise continuous-time Markov chains are a robust type of continuous-time Markov chains that allo...
We study the average behaviour of imprecise Markov chains; a generalised type of Markov chain where ...
The objective of our research is first of all the development of a method for learning the transitio...
AbstractWe consider convergence of Markov chains with uncertain parameters, known as imprecise Marko...
Many Markov chains with a single absorbing state have a unique limiting conditional distribution (LC...
AbstractThe parameters of Markov chain models are often not known precisely. Instead of ignoring thi...
Many Markov chains with a single absorbing state have a unique limiting conditional distribution (LC...
When the initial and transition probabilities of a finite Markov chain in discrete time are not well...
An imprecise Markov chain is defined by a closed convex set of transition matrices instead of a uniq...
Recently, Elmes et al. (see [2]) proposed a definition of a quasistationary distribution to accommod...
When the initial and transition probabilities of a finite Markov chain in discrete time are not we...
Recently, Elmes, Pollett and Walker [2] proposed a definition of a quasistationary distribution to a...
This paper proposes a method for fitting a two-state imprecise Markov chain to time series data from...
This paper proposes a method for fitting a two-state imprecise Markov chain to time series data fro...
In this thesis, we explore Markov chains with random transition matrices. Such chains are a developm...
Imprecise continuous-time Markov chains are a robust type of continuous-time Markov chains that allo...
We study the average behaviour of imprecise Markov chains; a generalised type of Markov chain where ...
The objective of our research is first of all the development of a method for learning the transitio...
AbstractWe consider convergence of Markov chains with uncertain parameters, known as imprecise Marko...
Many Markov chains with a single absorbing state have a unique limiting conditional distribution (LC...
AbstractThe parameters of Markov chain models are often not known precisely. Instead of ignoring thi...
Many Markov chains with a single absorbing state have a unique limiting conditional distribution (LC...
When the initial and transition probabilities of a finite Markov chain in discrete time are not well...
An imprecise Markov chain is defined by a closed convex set of transition matrices instead of a uniq...
Recently, Elmes et al. (see [2]) proposed a definition of a quasistationary distribution to accommod...
When the initial and transition probabilities of a finite Markov chain in discrete time are not we...
Recently, Elmes, Pollett and Walker [2] proposed a definition of a quasistationary distribution to a...
This paper proposes a method for fitting a two-state imprecise Markov chain to time series data from...
This paper proposes a method for fitting a two-state imprecise Markov chain to time series data fro...
In this thesis, we explore Markov chains with random transition matrices. Such chains are a developm...
Imprecise continuous-time Markov chains are a robust type of continuous-time Markov chains that allo...
We study the average behaviour of imprecise Markov chains; a generalised type of Markov chain where ...
The objective of our research is first of all the development of a method for learning the transitio...