An embedded and charset-unspecified text was scrubbed... Name: not available Url: https://stat.ethz.ch/pipermail/r-help/attachments/20080305/bca59e64/attachment.pl
non-linear correlation
2 messages · Irene Mantzouni, David Hewitt
Which effect sizes (parametric or not) could I use in order to estimate the amount of non-linear correlation between 2 variables? Is it possible to correct for auto-correlation within the correlated times series?
I think the starting point is to develop a model, even conceptual, of how you expect them to be related. If you've already determined that they are related, and in a way that's nonlinear, then you can probably come up with a model. "Effect size" will be dependent on the model, but in a nonlinear model it won't be as simple as "y goes as x goes". I can't see what you mean concerning the autocorrelation, but if this is a time series problem your first question is then a mystery to me. You might do well to read the posting guide for the mailing list and provide an example. ----- David Hewitt Virginia Institute of Marine Science http://www.vims.edu/fish/students/dhewitt/
View this message in context: http://www.nabble.com/non-linear-correlation-tp15848891p15852484.html Sent from the R help mailing list archive at Nabble.com.