similar to: glmnet: obtain predictions using predict and also by extracting coefficients

In the package lasso2, there is a Prostate Data. To find coefficients in the prostate cancer example we could impose L1 constraint on the parameters. code is: data(Prostate) p.mean <- apply(Prostate, 5,mean) pros <- sweep(Prostate, 5, p.mean, "-") p.std <- apply(pros, 5, var) pros <- sweep(pros, 5, sqrt(p.std),"/") pros[, "lpsa"] <-

Hi, First, when I try the example Prostate with bound 0.44 (as in the manual), I got a different result: > l1c.P <- l1ce(lpsa ~ ., Prostate, bound=0.44) > l1c.P .... Coefficients: (Intercept) lcavol lweight age lbph svi 1.0435803 0.4740831 0.1953156 0.0000000 0.0000000 0.3758199 lcp gleason pgg45 0.0000000 0.0000000

In an .Rd example for a package, I want to use data from another package, but avoid loading the entire package and avoid errors/warnings if that other package is not available. If I don't care about loading the other package, I can just do: if (require("ElemStatLearn", quietly=TRUE)) { data(prostate) # rest of example } I'd rather just be able to do something like:

Hi Everyone, I have a question regarding the construction of 3D graphs in 'R', BUT these graphs also need to illustrate movement (with time) of the prostate gland (using radiological techniques). I am not sure how to do this in 'R' although I'm sure there is some way of doing it. Below, I have copied and pasted some of the data with which I'm working on. The data

Describe fails for me with a message similar to what was an issue in 2008 and got fixed according to posts. R version 2.15.0 (2012-03-30) Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i386-pc-mingw32/i386 (32-bit) # output truncated > options(chmhelp = FALSE, help_type = "text") > .help.ESS <- help >

Dear all, I did post this more or less identical mail in a follow up to another question I posted, but under another heading. I try again, but now under the correct header. upon running this code (from the Hmisc library-latex function) I believe the call to summary.formula is allright and produces wonderful tables, but the latex command results in a correct formatted table but where all the

Dear Asterisk Community, Does your company provide inbound 800# origination? If so, please read this message and e-mail us a quote for monthly co-lo hosting of our asterisk server and per-minute inbound 800# origination. The Prostate Cancer Research and Education Foundation (PC-REF) is a non-profit organization dedicated to helping prostate cancer sufferers and their loved ones. We have

I have the following files list: > list.files() [1] "Prostate-Cancer_cvs_Dir" [2] "Prostate_Cancer-miRNAs&Genes.Pathway.xml" [3] "Prostate_Cancer_Pathways-miRNAs-GeneTargets-Dir" [4] "Prostate_Cancer_Pathways-miRNAs-GeneTargets-Dir.zip" [5] "Prostate-miRNAs.OrganTargets.txt"

Full_Name: Kem Phillips Version: 2.7.1 (2008-06-23) OS: Windows Xp professional Submission from: (NULL) (98.221.200.108) The Hmisc function describe fails, giving the error message: Error in formatDateTime(dd, atx, !timeUsed) : could not find function "format.dates" Loading the chron package, where function dates apparently resides, does not fix the problem. Note

Dear All, I'm reading Frank Harrell's wonderful Regression Modeling Strategies book and ran into a problem following the example in Chapter 8. I'm working on platform: Ubuntu 8.04 (i486-pc-linux-gnu) R version: 2.7.2 (2008-08-25) and my command sequence was: library(chron) library(Hmisc) load("prostate.sav") describe(prostate) The last command returned the error

Hi, I've lost my mind on it... I have to scatterplot two vectors, grouped by a third variable, with two different dimensions according to whether each cell line in the plot is sensitive or resistant to a given drug, and with a different color for each of 9 tissues of origin. Here's what I've done:

Hi everybody, this is a real dummy thing. I sorted a matrix based on a given column, and what I get is right, until it comes to columns of negative and positive values; than, "order" orders everything from max to min in the negative values, and then AGAIN from max to min in the positive values!!! Why isn't everything order from max to min, and that's it? Thank you!!! Attached

Sir, I found your description of the dataset about nodal involvement in prostate cancer. It comes from the book biostatistics casebook. I like to use the dataset for doing logistics regression. Can you tell me where I can find the dataset. Thanks and greetings Wim van Baarle wvbaarle@wxs.nl [[alternative HTML version deleted]]

Dear Rexperts, I am trying to add a '+' identifying the mean in a boxplot using the following sizelist <- split(size, grp) centers <- boxplot(sizelist, style.bxp = "att", medpch = "o", ylab = "Prostate Volume (cm3)") points(centers, unlist(lapply(sizelist, mean)), pch = "+") But, I get error Error in xy.coords(x, y) :

Hi, everyone: I ask for help about translating a stata program into R. The program perform cross validation as it stated. #1. Randomly divide the data set into 10 sets of equal size, ensuring equal numbers of events in each set #2. Fit the model leaving out the 1st set #3. Apply the fitted model in (2) to the 1st set to obtain the predicted probability of a prostate cancer diagnosis. #4. Repeat

Hi, I am interested in using the cast function in R to perform some aggregation. I did once manage to get it working, but have now forgotten how I did this. So here is my dilemma. I have several thousands of probes (about 180,000) corresponding to each gene; what I'd like to do is obtain is a frequency count of the various occurrences of each probes for each gene. The data would look

Dear R users, I am a new R user and something stops me when I try to write a academic article. I want to make a nomogram to predict the risk of prostate cancer (PCa) using several factors which have been selected from the Logistic regression run under the SPSS. Always, a calibration plot is needed to validate the prediction accuracy of the nomogram. However, I tried many times and read a lot of

Hi, See below I reply your message for <https://stat.ethz.ch/pipermail/r-help/2008-April/160966.html>[R] predict.glm & newdata posted on Fri Apr 4 21:02:24 CEST 2008 You say it ##works fine but it does not: if you look at the length of yhat2, you will find 100 and not 200 as expected. In fact predict(reg1, data=x2) gives the same results as predict(reg1). So I am still looking for

Dear R-helper, How could I count only some variable was exist after running sample (random) function. For example, > testx <- factor(c("Game","Paper","Internet","Time","Money")) > for(i in 1:2) { + x <- sample(testx,replace=TRUE) + print(x) + } [1] Money Money Time Internet Time Levels: Game Internet

Hello Please see the example below > class(testX) [1] "matrix" > class(testX[1,]) [1] "numeric" Why not matrix? What am I missing here? Is there a way to keep the same class? The reason for the question is that I want to implement a k-step ahead prediction for my own routines and R wrecks does not seem to like [1,] as shown below. >