ANALYSIS OF REPEATED MEASUREMENTS WITH MULTIVARIATE t OR CONTAMINATED MULTIVARIATE NORMAL ERRORS

DOI
  • Yamaguchi Kazunori
    Department of Information Systems, Interdisciplinary Graduate School of Engineering Sciences, Kyushu University

Bibliographic Information

Other Title
  • 誤差項に多変量t分布と混淆多変量正規分布を仮定した経時測定データの解析

Abstract

The analysis of repeated measurements is studied on the situation where there are some outliers which deviate so much from the other data as to arouse suspicions that they were generated by different mechanisms. In these case, if we use distributions which are heavy-tailed relative to the normal distribution as the assumed error distributions, the estimates might be less affected by outliers. From this point of view, we assume scale mixtures of multivariate normal distributions as the error distributions. Also, we consider the case with missing observation and propose a method to obtain the maximum likelihood estimates by applying the EM algorithm. Model selection by AIC and detection of outliers are also discussed with the aid of real data.

Journal

Keywords

Details 詳細情報について

  • CRID
    1390282679359110784
  • NII Article ID
    110001236569
  • DOI
    10.20551/jscswabun.3.1_11
  • ISSN
    21899789
    09148930
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

Report a problem

Back to top