Add to ORKGThe problem of a change in the mean of a sequence of random variables at an unknown time point has been addressed extensively in the literature. But, the problem of a change in the variance at an unknown time point has, however, been covered less widely. This paper analyses a sequence of autoregressive, AR(p), time series model in which the variance may be subjected to multiple changes at an unknown time points. Posterior distributions are found both for the unknown points of time at which the changes occurred and for the parameters of the model. A numerical example is also discussed
Autoregressive (AR), moving-average (MA), and autoregressive- moving average (ARMA) models are very ...
A Bayesian approach to the analysis of AR time series models, which permits the usual stationarity a...
AbstractAutoregressive time series models of order p have p+2 parameters, the mean, the variance of ...
The problem of a change in the mean of a sequence of random variables at an unknown\ud time point ha...
The problem of a change in the mean of a sequence of random variables at an unknown time point has b...
The problem of a change in the mean of a sequence of random variables at an unknown time point has b...
The problem of a change in the mean of a sequence of random variables at an unknown time point has b...
The problem of a change in the mean of a sequence of random variables at an unknown time point has b...
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered t...
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered t...
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered t...
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered t...
We examine autoregressive time series models that are subject to regime switching. These shifts are ...
In this paper, we discuss the problem of gradual changes in the parameters of an autoregressive (AR)...
AbstractThis paper analyses the asymptotic behaviour of the so-called a posteriori probabilities in ...
Autoregressive (AR), moving-average (MA), and autoregressive- moving average (ARMA) models are very ...
A Bayesian approach to the analysis of AR time series models, which permits the usual stationarity a...
AbstractAutoregressive time series models of order p have p+2 parameters, the mean, the variance of ...
The problem of a change in the mean of a sequence of random variables at an unknown\ud time point ha...
The problem of a change in the mean of a sequence of random variables at an unknown time point has b...
The problem of a change in the mean of a sequence of random variables at an unknown time point has b...
The problem of a change in the mean of a sequence of random variables at an unknown time point has b...
The problem of a change in the mean of a sequence of random variables at an unknown time point has b...
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered t...
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered t...
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered t...
This paper is a generalization of earlier studies by Venkatesan and Arumugam (2007) who considered t...
We examine autoregressive time series models that are subject to regime switching. These shifts are ...
In this paper, we discuss the problem of gradual changes in the parameters of an autoregressive (AR)...
AbstractThis paper analyses the asymptotic behaviour of the so-called a posteriori probabilities in ...
Autoregressive (AR), moving-average (MA), and autoregressive- moving average (ARMA) models are very ...
A Bayesian approach to the analysis of AR time series models, which permits the usual stationarity a...
AbstractAutoregressive time series models of order p have p+2 parameters, the mean, the variance of ...