search for: mydists

In qqmath, how would one go about having 'distribution' change with panel.number? I've tried set.seed(1) mydata <- data.frame(ind = factor(rep(2:4, each = 100))) mydata$val <- rt(300, df=rep(2:4, each = 100)) plot<-qqmath(~ val | ind, layout=c(3,1), data = mydata, prepanel = function(x, distribution, ...) {

Hello! I created a distances matrix for 13 objects using daisy (see the attached file). I am trying to clusteranalyse it using agnes but it's not working. What might be the problem: mydistances<-read.csv("Results of daisy.csv") mycluster<-agnes(mydistances, method="ward") I am getting: Error in agnes(mydistances, method = "ward") : NA/NaN/Inf in foreign

I also have several packages in my RW0633 in Windoze and I would like to keep them in one place when I update the R system. Brian say to modify Rprofile to ..lib.loc <- c("c:/MyR/library",.Library) now Rprofile has a line like .lib.loc <- unique(c(unlist(strsplit(getenv("RLIBS"),":")),.Library) Sorry to be dense but where should I put the

Hi, a couple of questions on manipulating a dataframe: 1) Without using a for loop (often inefficient, as i understand, in R), is it possible to split a dataframe into a list of dataframes with the number of *columns* in each (child)dataframe specified by the elements of a numeric vector? for example: dataframe 10 20 30 40 24 90 34 12 12 44 67 77 split using the vector c(3, 1) results in 2

I'm writing R code to calculate Hierarchical Social Entropy, a diversity index that Tucker Balch proposed. One article on this was published in Autonomous Robots in 2000. You can find that and others through his web page at Georgia Tech. http://www.cc.gatech.edu/~tucker/index2.html While I work on this, I realize (again) that I'm a C programmer masquerading in R, and its really

I am trying to fit a lognormal distribution to a set of data and test its goodness of fit with regard to predicted values. I managed to get so far: > y <- c(2,6,2,3,6,7,6,10,11,6,12,9,15,11,15,8,9,12,6,5) > library(MASS) > fitdistr(y,"lognormal",start=list(meanlog=0.1,sdlog=0.1)) meanlog sdlog 1.94810515 0.57091032 (0.12765945) (0.09034437) But I would

...(Y) and I can happily now run either hclust(X) or agnes(X). So that the various bits of output are labelled correctly I would dearly like to be able to give names to the columns and rows of X, as would happen if I ran: mydata<-read.table("clipboard",header=T) mydata2<-t(mydata) mydists<-dist(mydata2) Many thanks for your help. Best wishes, Kris Lockyear.

Hi All, I have my own distribution CD for RH 7.2 . and when i am i trying creted for CentOS i am facing some problem . I am not able to change the anaconda installer . Thanks in advance Regards juliet

Hi, can anyone help me in this problem :(. I am a total beginner in R software. It took me 2 days just to look into this problem. Due to this problem. I cant do looping. i want to find the distance between x and DSi > DSi i Si 1 1 (5, 20) 2 2 (20, 2) 3 3 (25, 32) 4 4 (8, 39) 5 5 (10, 17) 6 6 (35, 20) 7 7 (38, 10) > str (DSi) 'data.frame': 7 obs. of 2 variables: $ i

I couldn't resist tossing in my two-cents' worth on this, because R has some language features that allow you to use efficient optimization routines in a straightforward, elegant way. I'm particularly enthusiastic about this because I have suffered through other languages, which made this approach either painful or impossible, depending on the problem. Thanks to the R development

Hi there, Sorry if this is a rather loing post. I have a simple list of single feature data points from which I would like to generate a probability that an unseen point comes from the same distribution. To do this I am trying to estimate the probability density of the list of points and use this to generate a probability for the new unseen points. I have managed to use the R density function to

I have some data which I am trying to fit with a negative binomial distribution. I have found the glm.nb function from MASS. I have reason to believe that the mean parameter mu depends on certain factors, and that the shape parameter theta depends on others. If, say, the factors are P and Q, it might be that mu ~ P:Q and theta ~ P (where mu ~ P:Q means that mu is a function of the pair (P,Q))

Good morning, I am analyzing a dataset composed by 364 subjects and 13 binary variables (0,1 = absence,presence). I am testing possible association (co-presence) of my variables. To do this, I was trying with cluster analysis. My main interest is to check for the significance of the obtained clusters. First, I tried with the pvclust() function, by using method.hclust="ward" and

Hi everyone, I want to create my own distance measure, other than 'euclidean' or 'manhatan', to use in cluster pckgs. To do this I think that I need to change dist(), in mva pckg, or daisy(), in cluster pckg. (or is there a cleaver way ?) But this functions are in fact things like: .Fortran( "daisy", ... ) or .C("dist",...). I tried unsuccessfully to find

Use something like hclust(as.dist(mydist), ...) ought to work. Andy -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of ucecgxu at ucl.ac.uk Sent: Wednesday, January 18, 2006 4:47 PM To: r-help at stat.math.ethz.ch Subject: [R] r-help, how can i use my own distance matrix without using dist() Dear R-helpers, i am a

Hi, I'm trying to write a function to determine the euclidean distance between x (one point) and y (a set of n points). How should I pass y to the function? Until now, I used a matrix like that: | [,1] [,2] [,3] [1,] 0 2 1 [2,] 1 1 1 | Which would pass the points (0,2,1) and (1,1,1) to that function. However, when I pass x as a normal (column) vector,