![]() ![]() ![]() ![]() Partial Least Squares regression model equations The algorithms used by XLSTAT are such that the PLS1 is only a particular case of PLS2. PLS2 corresponds to the case where there are several dependent variables. PLS1 corresponds to the case where there is only one dependent variable. Some programs differentiate PLS1 from PLS2. The idea behind the PLS regression is to create, starting from a table with n observations described by p variables, a set of h components with the hPLS1 and PLS2 algorithms It is recommended in cases of regression where the number of explanatory variables is high, and where it is likely that the explanatory variables are correlated. Partial Least Squares regression (PLS) is a quick, efficient and optimal regression method based on covariance. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |