Effect of Correlation on the Estimation of a Mean in the Presence of Spurious Observations.

Abstract

This paper examines the effect of various correlation structures of observations on rules for estimating a mean which are designed to quard against the possibility of spurious observations (that is, observations generated in a manner not intended). The premium and protection of these rules are evaluated and discussed for the equi-correlation case and for the case of an autoregressive process of first order. It is shown that the premium and protection of a given rule which is designed for the estimator of a general mean mu when spuriosity may exist and when the observations are independent, lacks robustness to departures from independence. It is also shown that in moderate sized samples a spurious observation could seriously bias the usual estimator of the autoregressive coefficient alpha. One application of these results is in the case of a first order autoregressive model which can be used to represent many time series data encountered in business and economics.

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1975
Accession Number
ADA020212

Entities

People

  • G. C. Tiao
  • Irwin Guttman

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Coefficients
  • Commerce
  • Data Acquisition
  • Economics
  • Estimators
  • Observation

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Statistical inference.
  • Systems Analysis and Design