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...R data frame temporarily to the query in a transparent fashion. If not, I will see if I can create/drop the temp table directly from sqlQuery. > > > -Avram > > > > > > > > > > > > On Thursday, September 11, 2008, at 12:07PM, "Aaron Mackey" <ajmackey at gmail.com> wrote: > > >>Sorry, I see now you want to avoid this, but you did ask what was the > > >>"best way to efficiently ...", and the temp. table solution certainly > > >>matches your description. What's wrong with using a temporary tabl...

There's got to be a better way to use order() on a matrix than this: > y 2L-035-3 2L-081-23 2L-143-18 2L-189-1 2R-008-5 2R-068-15 3L-113-4 3L-173-2 398 1 1 2 2 1 1 2 2 857 1 1 2 2 1 2 2 2 911 1 1 2 2 1 2 2 2 383 1 1

I have a fairly large model: > length(Y) [1] 3051 > dim(covariates) [1] 3051 211 All of these 211 covariates need to be nested hierarchically within a grouping "class", of which there are 8. I have an accessory vector, " cov2class" that specifies the mapping between covariates and the 8 classes. Now, I understand I can break all this information up into individual

Dear All, I want to generate survival curve with cox model but I want to estimate the coefficients using glmnet. However, I also want to include a strata() term in the model. Could anyone please tell me how to have this strata() effect in the model in glmnet? I tried converting a formula with strata() to a design matrix and feeding to glmnet, but glmnet just treats the strata() term with one

(I think) I'd like to use the hmm.discnp package for a simple discrete, two-state HMM, but my training data is irregularly shaped (i.e. the observation chains are of varying length). Additionally, I do not see how to label the state of the observations given to the hmm() function. Ultimately, I'd like to 1) train the hmm on labeled data, 2) use viterbi() to calculate optimal labeling of