similar to: distances from points to line

Hi R help, I run my data in nnet with skip layer, factor response (with 0 & 1 values) and explicitly put softmax=T to compare the result of the default nnet with no softmax specification. I assume this should give me the same result. I got the result the default one, but not the softmax version and I got the error message that I did not quite understand. test6.nn.skipT.softm.Yfac <-

useR's, I would like to know if there is a way to avoid using FOR loops to perform the below calculation. Consider the following data: > x [,1] [,2] [,3] [1,] 4 11 1 [2,] 1 9 2 [3,] 7 3 3 [4,] 3 6 4 [5,] 6 8 5 > xk Var1 Var2 Var3 1 -0.25 1.75 0.5 2 0.75 1.75 0.5 3 1.75 1.75 0.5 4 2.75 1.75 0.5 5 3.75 1.75

Dear all, In lme, models in which a factor is fully "contained" in another lead to an error. This is not the case when using lm/aov. I understand that these factors are aliased, but believe that such models make sense when the factors are fitted sequentially. For example, I sometimes fit a factor first as linear term (continuous variable with discrete levels, e.g. 1,2,4,6), and

Dear list, I would like to expand a DF with all the missing levels of a variable. a <- c(2,2,3,4,5,6,7,8,9) a.cut <- cut(a, breaks=c(0,2,6,9,12), right=FALSE ) (x <- data.frame(a, a.cut)) # In 'x' the level "[0,2)" is "missing". AddMissingLevel <- function(xdf) { xfac <- factor( c("[0,2)", "[2,6)", "[6,9)",

I'm calling a list of symbols and then using a function to build a data frame from that symbol list. It works great until I introduce this index symbol from yahoo '^GSPC'. When and index symbol is introduced I get and error which is below. > Data <- symbolFrame(symbols) Error in get(S) : object '^GSPC' not found Since R does not like the ^ in front of a name it

Hi, in coxph, coxph(Surv(time, status)~x,data=alm). How to encode x? For example, if x has two groups, the treatment group and control group. if I encode them as 1 and 2. Is the HR results treatment/control? What if I encode them as 0 and 1. I am confused with how survival package works for HR. What should I do to get a treatment/control HR? Thank you. -- View this message in context:

I am new to R so I apologize if my question is trivial. I have not been able to figure out whether what I want to do is even possible. I have a data frame of stock ticker symbols which I store into R space from a txt file as follows: tickers <- read.csv("stocks.txt", header=FALSE, sep=",") tickers <- tickers[1] / the tickers are stored in the first column >

I checked the R procedure HCLUST (hierarchical clustering) but it looks like it requires a full triangular n x n similarity matrix as input, where n = number of observations. The number of variables is 200. My data set has n = 50,000 observations (keywords), and I use ad-hoc similarity measures, not available in R, to measure keyword similarity. Here, the vast majority of the n x n similarities

Easy one. I have win98 clients that login and connect to the shares fine. My problem is the user home directory, each user can see their folders and can even open them but they cannot save to their home directory. Each users home dir is setup as 0700 (-rwx------), as are the files and subdir's, which I believe is Read, Write, Execute for the owner of the file. What am I missing? Chris.

I keep getting the 'memory.size' error message when I run a program I have been writing. It always it cannot allocate a vector of a certain size. I believe the error comes in the code fragement below where I have multiple arrays that could be taking up space. Does anyone know a good way around this? w1 <- outer(xk$xk1, data[,x1], function(y,z) abs(z-y)) w2 <- outer(xk$xk2,

useR's, I am trying trying to find out if there is a faster way to do a certain computation. I have successfully used FOR loops and the apply function to do this, but it can take some time to fully compute, but I was wondering if anyone may know of a different function or way to do this: > x [1] 1 2 3 4 5 > xk [1] 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 I want to do:

Dear R-list, I'm trying to estimate the relative importance of 6 environmental variables in determining clam yield. To estimate clam yield a previous work used the function Yield = (A^a*B^b*C^c...)^1/(a+b+c+...) where A,B,C... are the values of the environmental variables and the weights a,b,c... have not been calibrated on data but taken from literature. Now I'd like to estimate the

Consider a data frame (x) with 2 variables, x1 and x2, having equal values. It looks like: x1 x2 1 1 2 2 3 3 Now, consider a second data frame (xk): xk1 xk2 0.5 0.5 1.0 0.5 1.5 0.5 2.0 0.5 0.5 1 1.0 1 1.5 1 2.0 1 0.5 1.5 1.0 1.5 1.5 1.5 2.0 1.5 0.5 2 1.0 2 1.5 2 2.0 2 I have written code to calculate some differences between these

Hi everyone, I want to convert an R function into VBA for calculating the eigenvectors and eigenvalues of a matrix using the "Power Method". The function is: PowerMethod <- function(x, tolerance) {     my.mat <- var(x[,-1], na.method="available")     matSize <- dim(my.mat)[1]     eigenVec <- matrix(NA, nrow=matSize, ncol=matSize)     eigenVal <- rep(NA,

Hello, I have a situation where a host, which is booted off its ''rpool'', need to temporarily import the ''rpool'' of another host, edit some files in it, and export the pool back retaining its original name ''rpool''. Can this be done ? Here is what I am trying to do: # zpool import -R /a rpool temp-rpool # zfs set mountpoint=/mnt

Greetings: I have what might be an oddball question. Is there any way to configure the times at which clients initiate their shutdown sequences? I have a domain controller in my setup that I would have shut down if the UPS have been on backup for any more than a minute, whereas the rest of the servers I would shut down on a low battery condition. I also have a use for such flexibility in our

Please suggest a way out to the following problem. I have a T by n data matrix (say Y) where coulmns are time series of length T. To do some analysis in WinBUGS I need to construct my data as follows. yy<-rep(Y,k) ## this will be a vector Yk<-array(yy,dim=c(T,n,k)) ## data array Here the definition of dim indices is first index: T rows second index: n columns third index: for kth T by n

R users: Thanks in advance  How to generate missing at random (MAR)? assaedi76@yahoo.com Thanks [[alternative HTML version deleted]]

Hi, could anyone explain to me what this warning message exactly means and what the consequences are? Is it due to the fact that there are very extreme observations / outliers included or what is the reason for it? Thanks so much, Werner Machen Sie Yahoo! zu Ihrer Startseite. Los geht's:

I'm pulling my hair (and there's not much left!) on this one. Basically I'm not getting the same result t when I "step" through the program and evaluate each element separately than when I use the outer() function in the FindLikelihood() function below. Here's the functions: Dk<- function(xk,A,B) { n0 *(A*exp(-0.5*(xk/w)^2) + B) } FindLikelihood <-