Understanding lasso error code

[Felix Bittmann]

Dear all,
consider the following example:

. clear all

. version 18.0

. set seed 123

. webuse nlswork
(National Longitudinal Survey of Young Women, 14-24 years old in 1968)

. lasso linear age c_city not_smsa collgrad, nolog

Lasso linear model                          No. of obs        =     28,502
                                            No. of covariates =          3
Selection: Cross-validation                 No. of CV folds   =         10

--------------------------------------------------------------------------
         |                                No. of      Out-of-      CV mean
         |                               nonzero       sample   prediction
      ID |     Description      lambda     coef.    R-squared        error
---------+----------------------------------------------------------------
       1 |    first lambda    1.074371         0       0.0001     44.90159
      60 |   lambda before    .0044393         3       0.0353     43.32257
    * 61 | selected lambda    .0040449         3       0.0353     43.32256
--------------------------------------------------------------------------
* lambda selected by cross-validation.
Note: Minimum of CV function not found; lambda selected based on stop()
      stopping criterion.

. di _rc
601

Apparently, the code runs fine and there are no error messages. Also, on the left side on the screen, after running lasso, there is no error code displayed for this command. Yet, _rc holds an error code. When I look up the code (601), this is: file not found (https://www.stata.com/manuals/perror.pdf#perror)

I am a bit confused what is going on. Is here an error? And if so, what exactly? Which file is not found?

[Jeff Pitblado (StataCorp)]

Stata's return code _rc (and c(rc)) is set by capture, and is not reset when a program calling it (capture) exits.

You should only check the value of _rc (or c(rc)) after using capture. Since you did not prefix lasso with capture, the value of _rc has no context for you.

[Felix Bittmann]

Thanks a ton for the clarification!