Asymptotic theory for the first projective direction

Michael G. Akritas

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


For a response variable Y, and a d dimensional vector of covariates X, the first projective direction, θ, is defined as the direction that accounts for the most variability in Y. The asymptotic distribution of an estimator of a trimmed version of θ has been characterized only under the assumption of the single index model (SIM). This paper proposes the use of a flexible trimming function in the objective function, which results in the consistent estimation of θ. It also derives the asymptotic normality of the proposed estimator, and characterizes the components of the asymptotic variance which vanish when the SIM holds.

Original languageEnglish (US)
Pages (from-to)2161-2189
Number of pages29
JournalAnnals of Statistics
Issue number5
StatePublished - Oct 2016

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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