Asymptotically Efficient Estimates of the Parameters of a Moving Average Time Series.

Abstract

The thesis is concerned with the estimation of the parameters of a moving average time series, (x sub t, t= 0, plus or minus 1, plus or minus 2, ...), of order M. By definition, such a series has the representation x sub t = (eta sub t) + (b sub 1)(eta sub (t-1)) + (b sub 2)(eta sub (t-2)) +...+ (b sub M)(eta sub (+-M)) for some series of uncorrelated, identically distributed random variables eta sub t, t = 0, plus or minus 1, plus or minus 2, ...). It is assumed that the process has mean zero and is a Gaussian process; hence eta sub t has a normal distribution with mean and some unknown variance (sigma sub n) squared. The goal is to find asymptotically normal and efficient estimates of the parameters of the model. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jul 31, 1970
Accession Number
AD0715129

Entities

People

  • M. Lawrence Clevenson

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Data Science
  • Distribution Functions
  • Functions (Mathematics)
  • Gaussian Distributions
  • Gaussian Processes
  • Information Science
  • Mathematics
  • Normal Distribution
  • Probability
  • Random Variables
  • Statistical Functions
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Statistical inference.