Partial least squares is an alternative to the multiple regressions which, in spite of using the original q explanatory variables directly, constructs the new set of k regressor variables as the linear combinations of the original variables. The linear combinations are selected sequentially in such a manner that each new regressor has maximal sample covariance with response variable subject to being uncorrelated with all the earlier constructed regressors.