similar to: scope of variable/object ?

Hi, I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using pamr.adaptthresh(): predicted true

Hi, I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using pamr.adaptthresh(): predicted true (1)

Hi, Sorry about the earlier formatting errors... I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using

Dear List, I am trying to modify the xlab and ylab for a current figure that was plotted by a package, I searched through the low level plotting command and they do not seem to contain how to do this (the only way is to use xlab, ylab as arguments in "plot" command, which I can not do since the plot is plotted using some other package, not by my own script). Is there any command for

Dear R-listers, I have created a plot to display the density lines for the same variable by different entities. Now, I want to fill the area under the density lines with semitransparent colors. Though I have checked that in web-searching and book-reading, I still do not perform that. Could anyone please give me any helps or advice? Thank you in advance. The data and code I used listed below: #

Dear R-listers, There is my data and my codes to create a plot. I want to know why there are two small circles in the upper right and lower left of the plot respectively. Could you please share your experience or advice with me? # dummy data factor<-rep(c("Alice","Jone","Mike"),each=100) factor<-factor(factor) traits<-c(rnorm(100, mean=1, sd=1), rnorm(100,

Dear maintainers and R-devel, Several orphaned CRAN packages are about to be archived due to outstanding QC problems, but have CRAN and BioC packages depending on them which would be broken by the archival (and hence need archiving alongside). Therefore we are looking for new maintainers taking over maintainership for one or more of the following packages: R2HTML SemiPar cghseg hexbin lgtdl

Dear Stuff, I am trying to enjoy "PAM", but I could not recognize which sample is in which branches in the clustering tree because of too many samples and size limitation for my monitor. I mean, I did unsupervised clustering with "PAM" ( data2$newy<-pamr.makeclasses(data2) ) with 275 primary samples, but samples were piled up at the point of each branch, so I cannot

Hello, I am writing an interface to some functions from the CRAN package pamr, which is poorly written. I have a S4 method I declared with setMethod. I'd like to provide a signature of "pamrtrained" which is the class of object that training creates. The last two lines of code of pamr.train are : class(junk) = "pamrtrained" junk How can I dispatch on these kinds

Dear R-help listers, I want to add 95% confidential interval as vertical lines to x axe in density plot. I have found the library(hdrcde) can do this work, but I do not know how to handle functions of this library when I used ggplot2 to draw the graph. Thank you in advance. The data and codes followed: # dummy data factor<-rep(c("Alice","Jone","Mike"),each=100)

Hi, I have tried some time trying to figure out how to use pamr to plot multiclass Estimated probabilities for the training data and test data? Specifically, how to recreate the PAMR publication on PNAS with Tibshrani et al. The publication is as attached. The plot I want to do is Figure 5. I have downloaded the pamr package and the function which gives similar plot is pamr.plotcvprob

1. According to the doc of PAMR, the shrinkage threshold is determined by cross-validation. Does this mean that user need not tune any parameter? 2. I tried two applications using PAMR, the results are very disappointing. The attached are the cross-validation results. You can see that the classification errors are relatively high (0.2 at the best), in the case of two categories classification,

I've started to implement checks for package versions on dependencies in install.packages(). However, this is revealing a number of problems/misconceptions. (A) We do not check versions when loading namespaces, ahd the namespace registry does not contain version information. So that for example (rtracklayer) Depends: R (>= 2.7.0), Biobase, methods, RCurl Imports: XML (>=

Dear R-help listers, Under the helps from the ggplot2 list, I have set up method of drawing a graph with multiple density plots arranged one by one in one page. Now, I want to add 95% confidential interval as vertical lines to x axe in density plot. I have found the library(hdrcde) can do this work, but I do not know how to handle functions of this library when I used ggplot2 to draw the graph.

Hello, I have binary labels from a nearest shrunken centroids prediction (package pamr). I need to obtain a ROC curve for this test. What is the easiest way to obtain one? Paolo Sonego

Hi, I am running R 2.2.0 on the Windows XP x64. The mechanism of error hanlder seems different. It will take a very long time to pop up a error message diaglog box, even when some simple errors happen such as "Syntax error" or "object xxxx not found". Does anybody have the similar experience? Thanks a lot. BTW: everything works fine under 32-bit Windows XP, error messages

Dear all, i searched for some classification methods and I have no glue if i took the right once. My problem: I have a matrix with 17000 rows and 33 colums (genes and patients). The patients are grouped into 3 diseases. No I want to classify the patients and for sure i want to know which rows are more helpful for the classification than others. I tried SVM and random forest. Do you think this

Art (and group), I'm doing this as a form of missing value analysis. Approximately 30% of the cases are missing data for one variable. To impute values for those cases, I'd like to match those cases that are missing the variable to all other cases and then take an average of those to infill. I realize there are many methods for imputing data. I'm not well versed on any in

Hello Guys I am facing a problem using cifs filesytem on centos 4.3 32 bit to connect to remote shares.we have DAS(Dell md1000) connected to a Dell 2950(win 2003 std).let me descibe the proc which i followed to access thi DAS via 2950.. 1) create a normal user account on Dell2950(win 2003) create 3 folders with names mysqhare1,myshare2,myshare3 in the storage area and assign all permissions to

I am working with microarray analysis and was using PAM with excel interface. Is there a way to do random divisions for the training set in excel? I also tried PAM in R with the pamr menu. How can I do the random divisions in R? Then I tried to reproduce "classification with gene expression data", which is chapter 24 from the book "bioinformatics and computational biology