similar to: rpart question

Sure I'm missing something simple here, but I haven't been able to find a easy way to convert a pure numeric (# of seconds since the beginning of 1970) back into a POSIX* object. ex. > z<-as.POSIXct(Sys.time()) > z [1] "2002-05-01 10:33:56 Mountain Daylight Time" > x<-unclass(z) > x [1] 1020270836 Is there a simple way to transform x back into a POSIX*

Hello, I have setup a samba server at my office as a PDC it stores the profiles on the server fine. I can access the profiles from any computer in the office just fine. My problem is that I work from home 4 days a week and need to access my work profile. I currently VPN into the office network via freeswan. I can log into the the domain from the vpn'd connection and I can access the samba

Dear list, after fitting an lrm with the Design package (stored as "mymodel") I try running a summary, but I get the following error: dim(mydata) [1] 235 9 names(mydata) [1] "id" "VAR1" "VAR2" "VAR3" "VAR4" "VAR5" "VAR6" "VAR7" "VAR8" summary(mymodel) Error in `contrasts<-`(`*tmp*`,

Ahh yes, sorry about that. Here's the corrected snippet: # Create an Example Data Frame Containing Car x Color data carnames <- c("bmw","renault","mercedes","seat") carcolors <- c("red","white","silver","green") datavals <- round(rnorm(16, mean=10, sd=4),1) data <- data.frame(Car=rep(carnames,4),

I have a substantial CSV to import but can't seem to import even the simplest CSV. I'm running the latest stable REvolution R on OS X if that is pertinent. Here's the contents of a simple test2.csv CSV file: #,Status,Project 5842,New,Test > snortalerts = read.table( "/Users/lcox/Documents/test2.csv", header=TRUE, > sep=",", row.names="#") Error

Hi, I've written a script that checks all bivariate correlations for variables in a matrix. I'm now trying to run a logistic regression on each pair (x,y) where y is a factor with 2 levels. I don't know how (or whether I want) to try to fathom what's up with glm. What I wrote is attached. Here's what I get. *****************************************************

I have some security alert log data that I'm parsing and doing some stats on. One of the fields is the "Classtype" which is the enumerated value of the type of alert found. classtypes = factor( alerts$Classtype ) fclass_types = table( classtypes ) fclass_types gives me a frequency table of the intrusion types: fclass_types classtypes

Dear R users, I am currently trying to create my first personnal function and use it with the apply function. The purpose of this function is to create a vector summarizing the number of levels in a given selection of data.frame columns. I tried to transpose the indexation method used by the nlevels function but it doesn't seem to work. I did not find anything uesful in the archives so

I'm trying to make a set of contour plots of bivariate kernel density estimates, showing three such plots overlaid, similar to this plot http://euclid.psych.yorku.ca/SCS/Private/Test/ridge-boot2.pdf except that I would like to have the contours *filled* (using transparent colors). To make this reproducible, I've saved the results of KernSmooth::bkde2D() in the following file:

I've been trying to understand the as.Date functionality and I have a date and time stamp field that looks like this: "Tue Sep 15 09:22:09 -0600 2009" and I need to turn it into an R Date object for analysis. Simple date conversions I have down, no problem: > adate = c("7/30/1959") > as.Date(adate,"%m/%d/%Y") [1] "1959-07-30" > But when it

Hello, This may not be a bug--but I'm not sure. I have R 1.91 installed on a machine that's running Windows XP. In Cygwin, when I attempt to use the "build" command it tells me that TMPDIR is set to an invalid directory. See the results below: stat20:/cygdrive/d/dirk/bands/implementation -> which r /cygdrive/d/Programs/R/rw1091/bin/r

Hi, I'd like to ask you a question again. It is basically about data frames, NAs and tabulate function. I have this data frame. I already used this in one of the previous questions of mine. It intentionally looks this simple, my real 'df' dataframe is much bigger actually and again, I am not willing to annoy anyone with huge databases... So, my database: id

Full_Name: Jens Lund Version: 1.3.1 OS: Windows Submission from: (NULL) (194.239.194.210) When we subset a dataset bartlett.test does not calculate the df correctly: X <- rnorm(50) # Generate simulated samples f <- gl(10,5) # Generate a factor with 10 levels and # 5 replications of each level # Works correctly bartlett.test(X,f) # Correct number of df = 9 #

I've written a piece of code (see below) to do a wavelet image decomposition, during the evaluation of this code I would like to write the results of some calculations back to the R root directory. I used assign() to do so because the names should vary when going thrue a while() loop. For some unknown reason I get an error that says: Error in assign(varname[i], imwrImage) :

Dear everyone, I am new in R and I've got difficulties in realizing the following tasks: -I have variables (factors) with different numbers of levels, either 1, 2 or 3. -I have a matrix containing these 204 factors and I have to correlate them by groups of 4 variables. -I have to delete the factors just having one level ( because when correlating one-level factors, the output is NA) here

Hello List! I asked this before (with no solution), but maybe this time... I'm trying to project a surface to the XY under a 3d cloud using lattice. I can project contour lines following the code for fig 13.7 in Deepayan Sarkar's "Lattice, Multivariate Data Visualization with R", but it fails when I try to "color them in" using panel.levelplot. ?utilities.3d says there

Hi, I'd like to compare SST data for year 2000 with SST for year 2001. I managed to get filled contour plots showing monthly SST for both years (12 plots for each year, 24 plots in total). In order to compare year 2000 and year 2001, however, I'd need to have the same legend scale (same color bar) in both years plots. Thus, my question is: is there a way to set the legend scale in

Hello, I came across a problem when building a randomForest model. Maybe someone can help me. I have a training- and a testdataset with a discrete response and ten predictors (numeric and factor variables). The two datasets are similar in terms of number of predictor, name of variables and datatype of variables (factor, numeric) except that only one predictor has got 20 levels in the training

Dear R-users, I have written the following code to generate some trellis plots. It works perfectly fine except that it is quite slow when it is apply to my typical datasets (over several thousands of lines). I believe the problem comes from the loops I am using to subset my data.frame. I read in the archives that the tapply function is often more efficient than a loop in R. Unfortunately ,

Hello there. I have fitted a rpart model. > rpartModel <- rpart(y~., data=data.frame(y=y,x=x),method="class", ....) and can use rpart$where to find out the terminal nodes that each observations belongs. Now, I have a set of new data and used predict.rpart which seems to give only the predicted value with no information similar to rpart$where. May I know how