Add to ORKGA new mathematical model of the s-order Markov chain with conditional memory depth is proposed. Maximum likelihood estimators of parameters are constructed and their properties are analyzed. A statistical test on parameter values is constructed. Numerical results are presented.BSU, INFOPAR
Accepted in Statistics & ComputingThis report addresses state inference for hidden Markov models. Th...
A limit theorem for the strongly regular semi-Markov process is proved under conditions C1 – C3
In this paper, we present a brief survey on the use of different types of Markov models in writing r...
In this talk I consider sequential Monte Carlo (SMC) methods for hidden Markov models. In the scenar...
An imprecise Markov chain is defined by a closed convex set of transition matrices instead of a uniq...
The paper deals with the problem of a statistical analysis of Markov chains connected with the spec...
We present an efficient exact algorithm for estimating state sequences from outputs (or observations...
We present an efficient exact algorithm for estimating state sequences from outputs (or observations...
Nonlinear Markov Chains (nMC) are regarded as the original (linear) Markov Chains with nonlinear sma...
In this note, we summarize briefly our series of studies on Markov dccision processes with unknown t...
Nonlinear regression model with continuous time and weak dependent or long-range dependent stationar...
AbstractA strongly ergodic non-homogeneous Markov chain is considered in the paper. As an analog of ...
In this paper, we study the behavior of second order pseudo-maximum likelihood estimators under cond...
When the initial and transition probabilities of a finite Markov chain in discrete time are not we...
In a previous paper, we have shown that forward use of the steady-state difference equations arising...
Accepted in Statistics & ComputingThis report addresses state inference for hidden Markov models. Th...
A limit theorem for the strongly regular semi-Markov process is proved under conditions C1 – C3
In this paper, we present a brief survey on the use of different types of Markov models in writing r...
In this talk I consider sequential Monte Carlo (SMC) methods for hidden Markov models. In the scenar...
An imprecise Markov chain is defined by a closed convex set of transition matrices instead of a uniq...
The paper deals with the problem of a statistical analysis of Markov chains connected with the spec...
We present an efficient exact algorithm for estimating state sequences from outputs (or observations...
We present an efficient exact algorithm for estimating state sequences from outputs (or observations...
Nonlinear Markov Chains (nMC) are regarded as the original (linear) Markov Chains with nonlinear sma...
In this note, we summarize briefly our series of studies on Markov dccision processes with unknown t...
Nonlinear regression model with continuous time and weak dependent or long-range dependent stationar...
AbstractA strongly ergodic non-homogeneous Markov chain is considered in the paper. As an analog of ...
In this paper, we study the behavior of second order pseudo-maximum likelihood estimators under cond...
When the initial and transition probabilities of a finite Markov chain in discrete time are not we...
In a previous paper, we have shown that forward use of the steady-state difference equations arising...
Accepted in Statistics & ComputingThis report addresses state inference for hidden Markov models. Th...
A limit theorem for the strongly regular semi-Markov process is proved under conditions C1 – C3
In this paper, we present a brief survey on the use of different types of Markov models in writing r...