REGRESSION AND AUTOREGRESSION WITH INFINITE VARIANCE.

Marek Kanter, W. L. Steiger

Research output: Contribution to journalArticlepeer-review

63 Scopus citations

Abstract

The theory of the linear model is incomplete in that it fails to deal with variables possessing infinite variance. To fill an important part of this gap, an unbiased estimate, the ″screened ratio estimate″ , is given for lambda in the regression E(X vertical Z) equals lambda Z; X and Z are linear combinations of independent, identically distributed symmetric random variables that are either stable or asymptotically Pareto distributed of index alpha less than equivalent to 2. The consistency of least squares estimates for finite moving averages is established.

Original languageEnglish (US)
Pages (from-to)768-783
Number of pages16
JournalAdvances in Applied Probability
Volume6
Issue number4
DOIs
StatePublished - 1974

All Science Journal Classification (ASJC) codes

  • Applied Mathematics
  • Statistics and Probability

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