Download 100 Years of Multivariate Analysis

100 Years of Multivariate Analysis
Ingram Olkin
Stanford University
ABSTRACT
The date of birth of a field is seldom well-defined. More usually there
are several key events from which a field then grows. In the case of
multivariate analysis, a distinguishing feature is the relation between
variables, and how are dependencies measured. Here the key
ingredient was the correlation coefficient introduced by Karl Pearson.
At that time there were no inferential methods, and here the year
1908 is important (exactly 100 years ago) with the introduction of
Student's t-statistic. This was a univariate procedure, but it was
needed before the next step could be taken. From this point onward,
multivariate procedures began to be developed. John Wishart
obtained the distribution of the sample covariance matrix, and this
was a central missing link for almost all future developments.
Although new multivariate methods have been developed over the
years, more recently there has been a resurgence of multivariate
procedures in finance and in data mining. In this talk I will walk
through some of the main ideas that have been the focus of research
in multivariate analysis.