Michael's -estsave- uses characteristics to
store e(stuff). So this exception is no
exception to the comment about -save-, but
a work-around.
e(sample) stays at least sometimes:
. sysuse auto, clear
. regress mpg weight if rep78 < .
. count if e(sample)
69
. preserve
. drop _all
. restore
. eret li
scalars:
e(N) = 69
e(df_m) = 1
e(df_r) = 67
e(F) = 123.808254590268
e(r2) = .6488621514626166
e(rmse) = 3.502097049675242
e(mss) = 1518.469087612675
e(rss) = 821.7338109380502
e(r2_a) = .6436212880516109
e(ll) = -183.3739540339589
e(ll_0) = -219.4808398939586
macros:
e(title) : "Linear regression"
e(depvar) : "mpg"
e(cmd) : "regress"
e(properties) : "b V"
e(predict) : "regres_p"
e(model) : "ols"
e(estat_cmd) : "regress_estat"
matrices:
e(b) : 1 x 2
e(V) : 2 x 2
functions:
e(sample)
. count if e(sample)
69
Nick
[email protected]
Richard Williams
> Actually, with Michael Blasnik's -estsave- routine (available from
> SSC) you can save estimation results with the current
> dataset. Although in the current example, I suppose a -restore-
> would wipe those out.
>
> As Zurab & Nick have already pointed out, you don't lose all the
> eclass stuff, just e(sample). As I stated before, my theory is that
> e(sample) would be too hard to keep, because of all the machinations
> that may have gone on with the data set in between the preserve and
> the restore.
>
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