`REG(f;s;m)`

indicates that the effects of factor `f`

are to be partitioned into the orthogonal regression contrasts specified by the first `s`

rows of the matrix `m`

. In regression models, the first argument may be a variate instead of a factor; `REG(v;s;m)`

then orthogonalizes and fits a set of associated variates stored in the first `s`

rows of the rows of the matrix `m`

. The matrix `m`

may be omitted in a regression model, in which case orthogonal polynomial contrasts are constructed for either `f`

or `v`

. Note, though, that the orthogonalization is with respect to the replication of the main effect of the factor or variate, so interactions of the contrasts with other vectors in a regression model may not be orthogonal.

# REG

Updated on December 4, 2017