Dear all, I am not sure if this is the right place to ask this question, but I will have a go. Please redirect me to a different place if this is not the right one!
I have a (relatively) simple problem which causes me some frustration because I cannot find the solution. I measure ten variables (var1 to var10) every day, they are all continuous (linear) and most of them are correlated. Some days, for any reason, the relationship between these variables may change. They are still correlated, but their correlation may change slightly but practically this is important. Or, one of the variables may increase its value significantly suddenly and keep this high value for a few days and then come back to the normal level. I am using R. Is there any function I can use to help me identify these strange days when the relationship between these variables changes? For example, if DayX is such a strange day, factor analyzing the data before DayX and after DayX separately would give me different factors (princial components). But how can I identify such a daym without trial and error? Thank you for the help... Dr. Iasonas Lamprianou Department of Social and Political Sciences University of Cyprus [[alternative HTML version deleted]]
______________________________________________ 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.