An autoregressive process of order one with double Lindley distribution as marginal is introduced. A mixture distribution is obtained for the innovation process. Analytical properties of the process are discussed. The parameters of the process are estimated and simulation studies are done. Practical application of the process is discussed with the help of a real data set
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-val...
1 Bayesian modeling of market price using autoregression model 1Šindelář Jan Department: Department ...
Abstract: Autoregressive processes are intensively studied in statistics and other fields of applied...
We introduce an autoregressive process called generalized normal-Laplace autoregressive process with...
We generalize the Gaussian mixture transition distribution (GMTD) model introduced by Le and co-work...
First order autoregressive process with semi-a-Laplace marginal distributions is developed. This ext...
Use of nonlinear models in analyzing time series data is becoming increasingly popular. This paper c...
Conditional heteroscedastic models are one important type of time series models which have been wide...
The log-Laplace distribution and its properties are considered. Some important properties like multi...
In recent years, many attempts have been made to find accurate models for integer-valued times serie...
In this paper, we reconsider the mixture vector autoregressive model, which was proposed in the lite...
In this paper we show that particular Gibbs sampler Markov processes can be modified to an autoregre...
Abstract. Suppose we observe a time series that alternates between different au-toregressive process...
We generalise the mixture autoregressive, MAR, model to the logistic mixture autoregressive with exo...
summary:The model of periodic autoregression is generalized to the multivariate case. The autoregres...
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-val...
1 Bayesian modeling of market price using autoregression model 1Šindelář Jan Department: Department ...
Abstract: Autoregressive processes are intensively studied in statistics and other fields of applied...
We introduce an autoregressive process called generalized normal-Laplace autoregressive process with...
We generalize the Gaussian mixture transition distribution (GMTD) model introduced by Le and co-work...
First order autoregressive process with semi-a-Laplace marginal distributions is developed. This ext...
Use of nonlinear models in analyzing time series data is becoming increasingly popular. This paper c...
Conditional heteroscedastic models are one important type of time series models which have been wide...
The log-Laplace distribution and its properties are considered. Some important properties like multi...
In recent years, many attempts have been made to find accurate models for integer-valued times serie...
In this paper, we reconsider the mixture vector autoregressive model, which was proposed in the lite...
In this paper we show that particular Gibbs sampler Markov processes can be modified to an autoregre...
Abstract. Suppose we observe a time series that alternates between different au-toregressive process...
We generalise the mixture autoregressive, MAR, model to the logistic mixture autoregressive with exo...
summary:The model of periodic autoregression is generalized to the multivariate case. The autoregres...
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-val...
1 Bayesian modeling of market price using autoregression model 1Šindelář Jan Department: Department ...
Abstract: Autoregressive processes are intensively studied in statistics and other fields of applied...