I need to measure kurtosis, skew, and maybe dip test on some distributions I have. Currently my data is in the form of 2 vectors x and y. Where x is 10 bins and y is the number of observations found in that bin. It seems that the measures I want to run require the actual observations laid out rather than already summed like I have them. Any suggestions on how to transform the data automatically? I have a semi- automated method in Excel but I think r will do a better job. I provide a more specific example below:
My csv file with the data looks like this: Bin: 1,2,3, ... ,10 #Observations: 23,42,1,... 56 I need this transformed into a single vector like this: c(1,1,1,1...2,2,2,2...3,...10,10,10,10...) The vector would have 23 "1"s, 42 "2s", 1 "3", etc. I actually have 68 of these vectors laid out in rows that I will measure separately, so my csv file actually looks like this: Bin: 1,2,3, ... ,10 #Observations: 23,42,1,... 56 Bin: 1,2,3, ... ,10 #Observations: 13,33,32,...98 . . . Bin: 1,2,3, ... ,10 #Observations: 11,76,55,...46 I want to automate the process. Thanks for any advice, kbrownk ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
