[R] analysis of circular data with mixed models???
Hi. I am trying to model data on movements (direction) of birds and the response variables are compass directions (0 to 360). I have found two packages CircStats and Circular that can implement linear models for a circular response, which will do what I need for the data set I am currently working on (modeling movements for only 1 species). However, in the near future, I would like to extend my modeling by including multiple species, and treating each species as a random effect. It appears that analysis of circular data using a mixed model approach is possible (see the text Statistical Analysis of Circular Data, Fisher 1996); however, does anyone know of a package in R that implements mixed models for circular data? Cheers -Steve __ 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.
[R] error propagation
Hello, I wish to examine the influence of error in variables on my analyses via error propagation. I have a data frame (x) as follows: id response 1-121 2-131 3-125 etc. I wish to propagate errors for each row in the data frame, where error is distributed around the value of the response variable. To do this, I wish to simulate 1000 variables for each row in the above data frame. I wrote the following, but suspect that it is not applying the function to each row sim-rnorm(1000,mean=x$response, sd= (rnorm(1000,mean= 9.454398, sd=1.980136))) Do I need to use tapply to have the function iteratively go through each row? Any advice would be appreciated. -Steve __ 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.
