search for: murphyk

I am having trouble installing the tree package on linux. I followed all the steps in section 5.2 of the FAQ http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html#How%20can%20add-on%20packages%20be%20installed%3f In particular, I typed 'R CMD INSTALL -l /home/cs/murphyk/R tree_1.0-2.tar.gz'. This created the files 'LibIndex', 'R.css' and a subdirectory called 'tree'. I then created a ~/.Renviron file with the line 'R_LIBS="/home/cs/murphyk/R"'. Inside R, I typed 'library()' and got back Packages in library...

I would like to specify that certain columns in a data frame should be treated as ordered factors. I know what numbers these columns are, but not their names. How do I do this? For example, if I know columns 1:4 are to be treated as factors, I can write dat <- matrix(c(2,1,1,1, 1,1,1,1), 2, 4) D <- as.data.frame(dat) # force all variables to be treated as binary # regardless of the small

...ted a regression tree using 4 predictors: 3 are unordered (binary) predictors, and the last is a date (integer), which I declare to be an ordered factor. However, the tree treats the date as if it were un-ordered, splitting into non-consecutive subsets. My code dat <- read.table("/home/cs/murphyk/R/Eugene/102.dat", header=TRUE) dat$machine <- factor(dat$machine) dat$TIM <- factor(dat$TIM) dat$lid <- factor(dat$lid) #dat$date <- factor(dat$date, ordered=TRUE) dat$date <- ordered(dat$date) tr <- tree(TRES ~ ., dat) produces 1) root 100 0.149300 0.2345 2) TIM: 11...

...ted a regression tree using 4 predictors: 3 are unordered (binary) predictors, and the last is a date (integer), which I declare to be an ordered factor. However, the tree treats the date as if it were un-ordered, splitting into non-consecutive subsets. My code dat <- read.table("/home/cs/murphyk/R/Eugene/102.dat", header=TRUE) dat$machine <- factor(dat$machine) dat$TIM <- factor(dat$TIM) dat$lid <- factor(dat$lid) #dat$date <- factor(dat$date, ordered=TRUE) dat$date <- ordered(dat$date) tr <- tree(TRES ~ ., dat) produces 1) root 100 0.149300 0.2345 2) TIM: 11...

I can build a tree at the command line using tr <- tree(V4 ~ ., dat) but I don't know how to build one inside a function - the following does not work foo <- function(dummy) { tr <- tree(V4 ~ ., dummy) } tr2 <- foo(dat) and produces the error Error in model.frame.default(formula = V4 ~ ., data = dummy) : Object "dummy" not found I know the solution has

The following code tr <- rpart(Y ~ ., dat, method="class") dev <- residuals(tr, "deviance") produces the following error Error in log(x) : Non-numeric argument to mathematical function > .Traceback [[1]] [1] "log(yhat)" # line 588 of rpart [[2]] [1] "switch(type, usual = as.integer(y != yhat), pearson = (1 - yhat)/yhat, " [2] "

Hi, I have noticed that aperm is very slow, and I wondered if there was a way of speeding it up. Let me tell you a bit about the context of my problem, because perhaps I shouldn't be using aperm at all. The context is probabilistic inference in graphical models. One of the most fundamental operations is two compute an element-wise multiplication of two arrays of different sizes, say A and B.

I have a question about what is considered good style in R. I have a function which returns several arguments, say [x,y,z]=f(), where sometimes I only care about the first few (so in Matlab, I can write e.g., [x,y] = f()). In R, there seem to be 2 ways to write this, both unsatisfying (to me): LIST f <- function() { ... list(x=x,y=y,z=z) } res <- f() x <- res$x; y <- res$y; z