Parameter Sensitivity In Multivariate Methods

Abstract

Multivariate analyses are descriptive models of data. Interpreting the parameters of such models requires knowing how much the fit of the model to the data is impaired by changes in the parameters. The relation of parameter change to loss of goodness of fit can be called parameter sensitivity. Formulas are presented for assessing the sensitivity of multiple regression weights and principal component weights.