
lsfit(x, y, wt = NULL, intercept = TRUE, tolerance = 1e-07,
yname = NULL)
wt
. If any observation has a missing value in any field, that observation
is removed before the analysis is carried out.
This can be quite inefficient if there is a lot of missing data. The implementation is via a modification of the LINPACK subroutines
which allow for multiple left-hand sides.lm
which usually is preferable;
ls.print
, ls.diag
.
##-- Using the same data as the lm(.) example:
lsD9 <- lsfit(x = unclass(gl(2, 10)), y = weight)
ls.print(lsD9)
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