Advertisement

Testing the Randomness of the Coefficients

  • Des F. Nicholls
  • Barry G. Quinn
Part of the Lecture Notes in Statistics book series (LNS, volume 11)

Abstract

As indicated in the previous chapter, the asymptotic results for the maximum likelihood estimates may be used to test certain hypotheses of interest. The condition (cii), however, which was assumed so as to obtain a standard central limit theorem for the maximum likelihood estimates, precludes the use of the theory derived in chapter 4 to test what is perhaps the most relevant hypothesis, namely that Σ = 0, that is, that the data come from a fixed coefficient autoregression. This chapter examines the testing of hypotheses in general, and in particular, two tests for the hypothesis that Σ = 0.

Keywords

Covariance Matrix Maximum Likelihood Estimate Symmetric Matrix Asymptotic Distribution Joint Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag New York Inc. 1982

Authors and Affiliations

  • Des F. Nicholls
    • 1
  • Barry G. Quinn
    • 2
  1. 1.Australian National UniversityCanberraAustralia
  2. 2.University of WollongongWollongongAustralia

Personalised recommendations