• Published 2010

Author Posting

@inproceedings{Yata2010AuthorP,
  title={Author Posting},
  author={Kazuyoshi Yata},
  year={2010}
}
In this paper, we investigate both sample eigenvalues and Principal Component (PC) directions along with PC scores when the dimension d and the sample size n both grow to infinity in such a way that n is much lower than d. We consider general settings that include the case when the eigenvalues are all in the range of sphericity. We do not assume either the normality or a ρ-mixing condition. We attempt finding a difference among the eigenvalues by choosing n with a suitable order of d. We give… CONTINUE READING