On simulation of first-order auto-regressive processes with near Laplace marginals

Author

Pawlak, Mirek ; Yahampath, Pradeepa

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Manitoba, Winnipeg, MB

fYear

2009

fDate

19-24 April 2009

Firstpage

3421

Lastpage

3424

Abstract

The focus of this paper is the modeling of a class of stationary non-Gaussian auto-regressive processes that often find applications in statistical signal processing. We propose a general simulation procedure for constructing a time series model with a near-Laplace marginal distributions. Our approach is based on a class of Monte Carlo rejection algorithms. A theoretical analysis of the average complexity of the proposed algorithms for simulating the time series model is included.

Keywords

Laplace equations; Monte Carlo methods; autoregressive processes; signal processing; statistical analysis; time series; Laplace marginal distribution; Monte Carlo rejection algorithm; stationary nonGaussian autoregressive process; statistical signal processing; time series model; Algorithm design and analysis; Analytical models; Computational modeling; Computer simulation; Density functional theory; Inverse problems; Monte Carlo methods; Signal processing algorithms; Speech analysis; Technological innovation; Laplace distribution; Monte Carlo; rejection algorithms; signal modeling; time series;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Conference_Location

Taipei

ISSN

1520-6149

Print_ISBN

978-1-4244-2353-8

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2009.4960360

Filename

4960360