A PCA-like method for multivariate data with missing values

研究成果: Article査読

8 被引用数 (Scopus)

抄録

This paper discusses the development of a PCA-like method being able to capture the structure of incomplete multivariate data without any statistical assumption such as a multivariate normal distribution or a random missing process. This method, purely descriptive, is derived from a lower rank approximation of a data matrix with missing values. Parameters are estimated by the Newton-Raphson method in order to minimize the least squares criterion with respect to observed values. Two examples of educational measurement are added to demonstrate practial use of the method.

本文言語English
ページ(範囲)257-265
ページ数9
ジャーナルJapanese Journal of Educational Psychology
40
3
DOI
出版ステータスPublished - 1992
外部発表はい

ASJC Scopus subject areas

  • 教育
  • 発達心理学および教育心理学

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