Hostname: page-component-848d4c4894-hfldf Total loading time: 0 Render date: 2024-06-03T04:26:40.726Z Has data issue: false hasContentIssue false
  • English
  • Français

First-order autoregressive logistic processes

Part of: Inference from stochastic processes Stochastic processes Probabilistic methods, simulation and stochastic differential equations

Published online by Cambridge University Press:  14 July 2016

C. H. Sim
C. H. Sim*
Affiliation:
University of Malaya
*
∗ Postal address: Department of Mathematics, Faculty of Science, University of Malaya, 59 100 Kuala Lumpur, Malaysia.
Get access Rights & Permissions [Opens in a new window]

Abstract

We propose an AR(1) model that can be used to generate logistic processes. The proposed model has simple probability and correlation structure that can accommodate the full range of attainable correlation. The correlation structure and the joint distribution of the proposed model are given, as well as their conditional mean and variance.

Keywords

BIVARIATE LOGISTIC DISTRIBUTIONSIMULATIONSTOCHASTIC MODEL

MSC classification

Primary: 62M10: Time series, auto-correlation, regression, etc.
Secondary: 65C20: Models, numerical methods 60G10: Stationary processes
Type
Short Communications
Information
Journal of Applied Probability , Volume 30 , Issue 2 , June 1993 , pp. 467 - 470
Copyright
Copyright © Applied Probability Trust 1993 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arnold, B. C. and Robertson, C. A. (1989) Autoregressive logistic processes. J. Appl. Prob. 26, 524–531.CrossRefGoogle Scholar
Lewis, P. A. W. (1985) Some simple models for continuous variate time series. Water Resources Bull. 21, 635–644.Google Scholar
Oberhettinger, F. (1973) Fourier Transforms of Distributions and Their Inverses. Academic Press, New York.Google Scholar
Rao, P. S. and Johnson, D. H. (1988) A first-order AR model for non-Gaussian time series. Proc. IEEE Int. Conf. on ASSP. 3, 1534–1537.Google Scholar