Add to ORKGA time-series model for Laplace (double-exponential) variables having second-order autoregressive structure (NLAR(2)) is presented. The model is Markovian and extends the second-order process in exponential variables, NEAR(2), to the case where the marginal distribution is Laplace. The properties of the Laplace distribution make it useful for modeling in some cases where the normal distribution is not appropriate. The time-series model has four parameters and is easily simulated. The autocorrelation function for the process is derived as well as third-order moments to further explore dependency in the process. The model can exhibit a broad range of positive and negative correlations and is partially time reversible.Office of Naval ResearchN...
The normal-Laplace distribution is considered and its properties are discussed. A multivariate norma...
This paper extends recent ideas for constructing classes of stationary autoregressive processes of o...
The classical autocorrelation function may not be an effective and informative means in revealing th...
The article of record as published may be found at https://doi.org/10.1109/TIT.1985.1057089A time-se...
An approach to modelling and residual analysis of nonlinear autoregressive time series in exponentia...
Generalizations and extensions of a first order autoregressive model of Lawrance and Lewis [Lawrance...
The log-Laplace distribution and its properties are considered. Some important properties like multi...
We introduce an autoregressive process called generalized normal-Laplace autoregressive process with...
We propose and study integer-valued time series models with the discrete Laplace marginal distributi...
In this paper we present a stationary Beta-Gamma autoregressive process of the second-order which re...
First order autoregressive process with semi-a-Laplace marginal distributions is developed. This ext...
Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{A...
A new class of time series models known as Generalized Autoregressive of order one with first-order ...
The paper considers the double-autoregressive model y(t) = phiy(t-1)+epsilon(t) with epsilon(t) = et...
An autoregressive process of order one with double Lindley distribution as marginal is introduced. A...
The normal-Laplace distribution is considered and its properties are discussed. A multivariate norma...
This paper extends recent ideas for constructing classes of stationary autoregressive processes of o...
The classical autocorrelation function may not be an effective and informative means in revealing th...
The article of record as published may be found at https://doi.org/10.1109/TIT.1985.1057089A time-se...
An approach to modelling and residual analysis of nonlinear autoregressive time series in exponentia...
Generalizations and extensions of a first order autoregressive model of Lawrance and Lewis [Lawrance...
The log-Laplace distribution and its properties are considered. Some important properties like multi...
We introduce an autoregressive process called generalized normal-Laplace autoregressive process with...
We propose and study integer-valued time series models with the discrete Laplace marginal distributi...
In this paper we present a stationary Beta-Gamma autoregressive process of the second-order which re...
First order autoregressive process with semi-a-Laplace marginal distributions is developed. This ext...
Abstract The paper studies the estimation and the portmanteau test for double AR(p) $\operatorname{A...
A new class of time series models known as Generalized Autoregressive of order one with first-order ...
The paper considers the double-autoregressive model y(t) = phiy(t-1)+epsilon(t) with epsilon(t) = et...
An autoregressive process of order one with double Lindley distribution as marginal is introduced. A...
The normal-Laplace distribution is considered and its properties are discussed. A multivariate norma...
This paper extends recent ideas for constructing classes of stationary autoregressive processes of o...
The classical autocorrelation function may not be an effective and informative means in revealing th...