Force variables into clogitL1 lasso model

I am running a conditional logistic regression on a case/control dataset and would like to use lasso for variable selection. I am currently using to use the clogitL1, but I do not see a way to force the inclusion of my control variables.
(1) Am I missing an option within the package that would allow me to force include specific parameters?
(2) Are there other packages of methodologies that I could accomplish this with?


data parameters

K = 10 # number of strata
n = 5 # number in strata
m = 2 # cases per stratum
p = 20 # predictors

generate data

y = rep(c(rep(1, m), rep(0, n-m)), K)
X = matrix (rnorm(Knp, 0, 1), ncol = p) # pure noise
strata = sort(rep(1:K, n))
par(mfrow = c(1,2))

fit the conditional logistic model

clObj = clogitL1(y=y, x=X, strata)
plot(clObj, logX=TRUE)

cross validation

clcvObj = cv.clogitL1(clObj)

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