I have a problem that deals with correlating wind velocity to seed collection data. The problem lies in that I have a wind data set that is contains 2000+ data points and weed collection data on the order of a couple hundred. Both data sets were collected for the same time period, but there is not a one-to-one wind velocity->seed location match. My understanding of correlation is that you need equal data sets. Is there a way to compare means and standard deviations (or kappa in circular stats) that doesn't require equal data sets? Thank you in advance. Joe
Example (simplified): library(CircStats) wind<-c(2.1, 2.3, 2.6, 2.1, 2.6, 2.4, 1.2, 1.5) # in radians seed<-c(1.7, 1.3, 1.5, 1.9, 1.8, 2.3) circ.cor(wind, seed, test=T) Joseph Dauer Master's Student Weed Ecology 412 ASI Pennsylvania State University University Park, PA 16802 email: [EMAIL PROTECTED] office phone: (814) 865 - 6679 http://www.agronomy.psu.edu/weedecology [[alternative HTML version deleted]] ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
