Keywords

Autoregressive models

Abstract

Consider a sequence of random variables which obeys a first order autoregressive model with unknown parameter alpha. Under suitable assumptions on the error structure of the model, the limiting distribution of the normalized least squares estimator of alpha is discussed. The choice of the normalizing constant depends on whether alpha is less than one, equals one, or is greater than one in absolute value. In particular, the limiting distribution is normal provided that the absolute value of alpha is less than one, but is a function of Brownian motion whenever the absolute value of alpha equals one. Some general remarks are made whenever the sequence of random variables is a first order moving average process.

Notes

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Graduation Date

2012

Semester

Spring

Advisor

Richardson, Gary

Degree

Master of Science (M.S.)

College

College of Sciences

Department

Mathematics

Degree Program

Mathematical Science; Industrial Mathematics

Format

application/pdf

Identifier

CFE0004276

URL

http://purl.fcla.edu/fcla/etd/CFE0004276

Language

English

Release Date

May 2015

Length of Campus-only Access

3 years

Access Status

Masters Thesis (Open Access)

Subjects

Dissertations, Academic -- Sciences, Sciences -- Dissertations, Academic

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Included in

Mathematics Commons

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