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Hi, I would like to display inter-parameter scatter plots like those with the corrgram package (see upper triangle here: http://www.statmethods.net/advgraphs/images/corrgram2.png ), just that I would like to plot two datasets instead of one. Say one with black and one with red dots. Or a merged dataset where an indicator column is used to assign different colors to particular dots - with still

Hi, For my data, I followed the example of http://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/K-Means#Execution and got some very nice results. Despite the fact, that I want to achieve a bit more by clustering my data (stratification beyond case-control), the actual data-frame contains a column labeled "C" which holds a case-control indicator (here either "Z"

Hi, Thanks Sarah. Unfortunately I did not get a step further. My question, perhaps a bit clearer, is how to display the case control status (or any other arbitrary point label) after clustering in a plot: With a bit of pseudo code, where dataset is a data.frame, parameters are those column names where we find numerical values (no NAs) and nclasses is the desired number of classes. fit <-

Hi, I would like to tabulate the likelihood for an affection. For this, I retrieve indices of affected people and controls for my data set and proceed as follows: flags <- c(rep(1, length(patient_indices)), rep(0, length(control_indices))) # dataset is a data.frame and param the parameter to be analysed: data1 <- dataset[,param][c(patient_indices, control_indices)] fit1 <- glm(flags ~

Hi, I have some questions for the wireframe function of the lattice package. My dataset's "x-data" are sampled logarithmically and as such I would like to have a semilogarithmic 3D plot when plotting a time series. Does anyone know how to change the example in http://addictedtor.free.fr/graphiques/sources/source_40.R such that x or y would be logarithmically scaled? Also, I would