Discrete Time Series Generated by Mixtures II: Asymptotic Properties
Loading...
Authors
Jacobs, Patricia A.
Lewis, Peter A.W.
Subjects
discrete time series
mixtures
asymptotic properties
mixed autoregressive-moving average
central limit theorems
goodness-of-fit
models
mixtures
asymptotic properties
mixed autoregressive-moving average
central limit theorems
goodness-of-fit
models
Advisors
Date of Issue
1977-04
Date
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
The DARMA (discrete mixed autoregressive‐moving average) processes are a broad but parametrically simple class of models for a stationary sequence of dependent discrete random variables. A darma process is formed as a random linear combination of independent identically distributed discrete random variables. The process is specified by the distribution of the independent variables, which is also the marginal distribution of the random process, and several other chosen parameters which independently determine the covariance structure of the process. In this paper the asymptotic properties of the darma process are studied. Limiting results for estimates of moments, percentiles and quantiles are obtained. Asymptotic properties of the χ2 test for goodness‐of‐fit for the marginal distribution of the process are also studied.
Type
Technical Report
Description
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
NPS55-77-17
Sponsors
Funder
Format
26 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.