similar to: variable type assignment in daisy

hi! i run quake2(an ooooold game) with wine, and it works perfectly with opengl and it seems to works ok, but, when i try to write something in the game-console i can't, i see the game but i can't use my keyboard on it. The same thing happen to me with jedi outcast II, i see the game but i can't use my keyboard.. the mouse works fine, but not the keyboard. thanks for your help.

Hello, I am running DAISY in R and using the GOWER metric since I am working with mixed variables. I am wondering if there is a way to weight the different variables. I see that there is a weight value for Gower but do not know if this is how to weight the diffrent variables with different weighting values. Please advise if there is a way to weight the different variables. Thank you. -- View

I am using DIANA/DAISY/GOWER. Some of my categorical data include NULLS. When assessing disimilarity, these NULLS are considered similar. I do not want these NULLS to contribute towards similarity. Instead is there a way for these NULLS to each be considered different so as to contribute to disimiliarity and not simillarity? Also, I do not want to change these NULLS in the data as I need them for

Dear R-helpers, First of all, a happy new year to everyone! I succesfully used the daisy function (from package cluster) to find which two rows from a dataframe differ by only one value, and I now want to come up with a simpler way to find _which_ value makes the difference between any such pair of two rows. Consider a very small example (the actual data counts thousands of rows): input

I am currently using the function daisy in package cluster to create a dissimilarity matrix because my multivariate dataset contain missing data and variables of various types including factors, symmetric and asymmetric binary and quantitative. This is a step prior to using pco within ecodist. There is a warning which comes twice ">NAs introduced by coercion" I've used

Hi, I'm trying to apply the function daisy() to a data.frame 10000x10 but I have not enough space (error message: cannot allocate vector of length 1476173280). I didn't imagine I was not able to work with a matrix of just 10000 observations... I have setted in Rgui --max-mem-size=2G (I'm not able to set more space..) How can I solve this issue? Separating observations depending on

Hi, I have two groups, and I want to find the dissimiarity between the members of the two groups. Since I have mixed level variables on the members, I opt for the daisy function in the cluster package. Let's pretend that the following represent my groups: x <- data.frame(sex=factor(c(1,0,0,1,0,1), levels=0:1, labels=c('Male','Female'), ordered=FALSE),

Hi All - I am using the daisy function from the cluster library to create a dissimilarity matrix. I'm going to use that matrix to run a cluster analysis. My participants are identified with the variable, hhid. However, when I try to keep hhid in the dataset that I use to create the dissimilarity matrix, daisy uses it to create the matrix rather than ignoring it as an ID variable. I need to

Hi, I'm using the cluster library to examine multivariate data. The data come from a connection to a postgres database, and I did a short R script to do the analisys. With the cluster version included in R1.8.0, daisy worked well for my data, but now, when I call daisy, I obtain the following messages: --------- Error in if (any(sx == 0)) { : missing value where TRUE/FALSE needed In

Hi, I'm a PhD student and I want to use the function 'daisy' from the package 'cluster' to compute dissimilarities. My variables are of mixed types so I use the argument 'stand' in daisy to define the type of my variables. I have the following error message : Warning message: binary variable(s) 13, 16, 17, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,

Hi, According to daisy function from cluster documentation, it can compute dissimilarity when NA (missing) value(s) is present. http://stat.ethz.ch/R-manual/R-devel/library/cluster/html/daisy.html But why when I tried this code library(cluster) x <- c(1.115,NA,NA,0.971,NA) y <- c(NA,1.006,NA,NA,0.645) df <- as.data.frame(rbind(x,y)) daisy(df,metric="gower") It gave this