Determining The Dimensionality In Sliced Inverse Regression
Abbreviated Journal Title
J. Am. Stat. Assoc.
EIGENPROJECTION; ELLIPTICALLY SYMMETRICAL DISTRIBUTION; GENERAL; REGRESSION MODEL; PROJECTION MATRIX; REDUCTION; Statistics & Probability
A general regression problem is one in which a response variable can be expressed as some function of one or more different linear combinations of a set of explanatory variables as well as a random error term. Sliced inverse regression is a method for determining these linear combinations. In this article we address the problem of determining how many linear combinations are involved . Procedures based on conditional means and conditional covariance matrices, as well as a procedure combining the two approaches, are considered. In each case we develop a test that has an asymptotic chi-squared distribution when the vector of explanatory variables is sampled from an elliptically symmetric distribution.
Journal of the American Statistical Association
"Determining The Dimensionality In Sliced Inverse Regression" (1994). Faculty Bibliography 1990s. 1172.