search for: coxnet

Dear all, I am using glmnet (Coxnet) for building a Cox Model and to make actual prediction, i.e. to estimate the survival function S(t,Xn) for a new subject Xn. If I am not mistaken, glmnet (coxnet) returns beta, beta*X and exp(beta*X), which on its own cannot generate S(t,Xn). We miss baseline survival function So(t). Below is my...

...rol() allows one to set internal parameters in glmnet, previously not under user control. These are for knowledgeable users. Once changed, the settings persist for the session. glmnet.control has a useful factory=TRUE argument, which will reset the "factory" defaults. * a memory bug in coxnet has been fixed. Trevor Hastie ---------------------------------------------------------------------------------------- Trevor Hastie hastie at stanford.edu Professor, Department of Statistics, Stanford University Phone: (650) 725-2231 Fax...

...rol() allows one to set internal parameters in glmnet, previously not under user control. These are for knowledgeable users. Once changed, the settings persist for the session. glmnet.control has a useful factory=TRUE argument, which will reset the "factory" defaults. * a memory bug in coxnet has been fixed. Trevor Hastie ---------------------------------------------------------------------------------------- Trevor Hastie hastie at stanford.edu Professor, Department of Statistics, Stanford University Phone: (650) 725-2231 Fax...

...pilepsy-free time is discrete. We suppose that we need to conduct a cox analysis with discrete time. Is that right? 3. We acquired quite a lot of image features, which makes the feature selection imperative. We have planned to use the Lasso penalty for feature selection. We notice that the 'coxnet'/'glmnet'/'penalized' package could be used to construct the Lasso-cox model. Are they still appropriate for the cox analysis with discrete time? Sorry for the poor English expression. We're still new to R. We're very grateful for any help. Thank you very much!...

Hello, I have a problem with creating an identity matrix for glmnet by using the contrasts function. I have a factor with 4 levels. When I create dummy variables I think there should be n-1 variables (in this case 3) - so that the contrasts would be against the baseline level. This is also what is written in the help file for 'contrasts'. The problem is that the function