Add to ORKGA new special case of high-order Markov chains with a small number of parameters – Markov chain of conditional order – is considered. Statistical estimators for parameters of the model by observed time series are constructed; their asymptotic properties are analyzed. Results of computer experiments are presented
<p>Using a parameterization as zeroth-order Markov chain as null hypothesis, we compared in the Baye...
Markov chains are a natural and well understood tool for describing one-dimensional patterns in time...
AbstractRecursive equations are derived for the conditional distribution of the state of a Markov ch...
The paper deals with Markov chain of conditional order, which is a special case of a high-order Mar...
The paper deals with finite Markov chain of conditional order, that is a special case of high-order ...
A new mathematical model of the s-order Markov chain with conditional memory depth is proposed. Maxi...
This paper deals with order identification for Markov chains with Markov regime (MCMR) in the contex...
This paper deals with order identification for Markov chains with Markov regime (MCMR) in the conte...
Problems of statistical analysis of discrete-valued time series are considered. A family of parsimon...
Statistical estimators for the parameters of the Markov chain of the s-th order with r partial conn...
In this thesis, the properties of some non-standard Markov chain models and their corresponding para...
The structural parameters of many statistical models can be estimated maximizing a penalized version...
Let {Y sub t} be a stationary stochastic process with values in the finite set YY. We model {Y sub t...
This paper describes a Bayesian approach to determining the order of a finite state Markov chain who...
The problem of sequential testing of hypotheses on parameters of Markov chains is considered. The sp...
<p>Using a parameterization as zeroth-order Markov chain as null hypothesis, we compared in the Baye...
Markov chains are a natural and well understood tool for describing one-dimensional patterns in time...
AbstractRecursive equations are derived for the conditional distribution of the state of a Markov ch...
The paper deals with Markov chain of conditional order, which is a special case of a high-order Mar...
The paper deals with finite Markov chain of conditional order, that is a special case of high-order ...
A new mathematical model of the s-order Markov chain with conditional memory depth is proposed. Maxi...
This paper deals with order identification for Markov chains with Markov regime (MCMR) in the contex...
This paper deals with order identification for Markov chains with Markov regime (MCMR) in the conte...
Problems of statistical analysis of discrete-valued time series are considered. A family of parsimon...
Statistical estimators for the parameters of the Markov chain of the s-th order with r partial conn...
In this thesis, the properties of some non-standard Markov chain models and their corresponding para...
The structural parameters of many statistical models can be estimated maximizing a penalized version...
Let {Y sub t} be a stationary stochastic process with values in the finite set YY. We model {Y sub t...
This paper describes a Bayesian approach to determining the order of a finite state Markov chain who...
The problem of sequential testing of hypotheses on parameters of Markov chains is considered. The sp...
<p>Using a parameterization as zeroth-order Markov chain as null hypothesis, we compared in the Baye...
Markov chains are a natural and well understood tool for describing one-dimensional patterns in time...
AbstractRecursive equations are derived for the conditional distribution of the state of a Markov ch...