[R] Glmnet Logistic Variable Questions

[Marc Schwartz]

On Oct 25, 2011, at 11:16 AM, Ben Bolker wrote:

> Bert Gunter <gunter.berton <at> gene.com> writes:
> 
>> 
>> If I understand you correctly, it sounds like you need to do some reading.
>> 
>> ?lm and ?formula tell you how to specify linear models for glm or glmnet.
>> However, if you do not have sufficient statistical background, It probably
>> will be incomprehensible, in which case you should consult your local
>> statistician.
>> 
>> For glmnet, go to the linked references given in the Help file.There is no
>> such thing as AIC for these models, as they are penalized fits (with users
>> choosing the penalization tradeoff). Again, consult your local statistician
> 
>  Let me second Bert's concern, but in the meantime, if what you
> want are *all two-way interactions among variables, you can follow
> this example:
> 
>> d <- data.frame(y=runif(100),x1=runif(100),x2=runif(100),x3=runif(100))
>> gg <- lm(y~(.)^2,data=d)
>> names(coef(gg))
> [1] "(Intercept)" "x1"          "x2"          "x3"          "x1:x2"      
> [6] "x1:x3"       "x2:x3"      
> 
> 
> I have done the example with continuous variables and with lm() here,
> but it should generalize easily to (1) a mixture of categorical and
> continuous variables and (2) other R modeling functions



There is a difference with glmnet however vis-à-vis its handling of factors. There is a recent discussion here:

  https://stat.ethz.ch/pipermail/r-help/2011-August/285905.html

which covers the topic. Be sure to read the replies, including Martin's.

HTH,

Marc Schwartz