`lambda.min.ratio` ignored by `glmnet` for `family = "binomial"`
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nhejazi commented
To achieve the quartic convergence rate dictated by theory, it is necessary to have the HAL regression function reach a saturated model asymptotically; however, this is currently not possible in the family = "binomial" implementation of glmnet(), as a call to glmnet() will ignore any specification of lambda.min.ratio in this case. This can be avoided in two ways: (1) setting family = "gaussian" and specifying a very low value of lambda.min.ratio (essentially a linear probability model in terms of HAL basis functions); or (2) directly passing in a sequence of L1 constraint parameters that includes a very low value through the lambda argument of glmnet(). Issue originally reported and confirmed by @idiazst.