similar to: Looking for new maintainer of orphans R2HTML SemiPar cghseg hexbin lgtdl monreg muhaz operators pamr

Hi All: Package TSERIES is stated to depend on MVA. However, there is no MVA package to be found under the list of package sources. Best wishes, ANDREW tseries: Package for time series analysis Package for time series analysis with emphasis on non-linear and non-stationary modelling Version: 0.7-6 Depends: ts, mva, quadprog Date: 2001-08-27 Author: Compiled by Adrian

Dear R users, I am trying to use "muhaz" and "plot.muhaz" functions in "muhaz" package to estimate and plot hazard funciton. However function "muhaz" always gives error message "Error in Surv(times, delta) : object "times" not found". I could not even run their sample codes in the user's manual as follows: data(ovarian)

Hi all, Does anyone know how to report heteroskedasticity and autocorrelation-consistent standard errors when using the "spm" command in SemiPar package? Suppose the original command is sp1<-spm(y~x1+x2+f(x3), random=~1,group=id) Any suggestion would be greatly appreciated. Thanks, Susan [[alternative HTML version deleted]]

Hello -- I posted this question yesterday and for some reason the post seems to be attached to the wrong thread. Also, I extended my test a little and it seems to indicate the problem is with spm. I would appreciate any help. Thanks. ========================================================== library(plyr) library(SemiPar) data <-

Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working

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

I'm taking the residual-regression approach to semiparametric estimation (Robinson 1988, Econometrica), and basically using SemiPar simply as a convenient means of doing multivariate nonparamteric additive models. The final bit of code is here: finalfit <- spm(res~f(V3,basis="trunc.poly")+f(V5,basis="trunc.poly")+f(V6,basis="trunc.poly")) summary(finalfit)

Hi, I must be missing something here...Essentially, a short piece of code works if it's standalone, but doesn't work if it's divided into two functions. The code that works is: ################### WORKS ############### library(pamr) set.seed(120) x <- matrix(rnorm(1000*20),ncol=20) y <- sample(c(1:4),size=20,replace=TRUE) mydata <- list(x=x,y=y)

Hi everyone: I want to fit the truncated polynomial smoothing to the quantiles instead of means, does someone know how to do it? I am thinking that maybe I can use SemiPar package, but can not find how. Thanks so many, Suyan

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,

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

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, Is it possible to create confidence intervals for hazard rates? ?I'm creating two muhaz objects:? haz1 <- muhaz(NumDaysCustomer[cRV=="true"],status[cRV=="true"]) haz2 <- muhaz(NumDaysCustomer[cRV=="false"],status[cRV=="false"]) and plotting them. ? There are many, many more observations in the cohort cRV=="false" than

Hello. ?I am hoping someone will be willing to help me understand something about hazard plots created with muhaz(...). ?I have some background in statistics (minor in grad school), but I haven't been able to figure one thing about hazard plots. ?I am using hazard plots to track customer cancellations. ?I figure I can treat a cancellation as a "death", and if someone is still a

Hello, If all I have access to is an empirically calculated hazard function, is it possible to compute an approximate value for the mean lifetime? I know that if the hazard function is essentially constant, the mean lifetime is 1/hazard rate. ?But if I'm confident that the empirical hazard function is not constant, I'm not sure how to go about calculating an estimate of mean lifetime.

Hi there, I am reading the 2004 paper "Smoothing with mixed model software" in Journal of Statistical Software, by Ngo and Wand. I tried to run their first example in Section 2.1 using R but I had some problems. Here is the code: library(nlme) fossil <- read.table("fossil.dat",header=T) x <- fossil$age y <- 100000*fossil$strontium.ratio knots <-