[This article was first published on Recology, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
A new paper out in Ecology by Xiao and colleagues (in press, here) compares the use of log-transformation to non-linear regression for analyzing power-laws.Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
They suggest that the error distribution should determine which method performs better. When your errors are additive, homoscedastic, and normally distributed, they propose using non-linear regression. When errors are multiplicative, heteroscedastic, and lognormally distributed, they suggest using linear regression on log-transformed data. The assumptions about these two methods are different, so cannot be correct for a single dataset.
They will provide their R code for their methods once they are up on Ecological Archives (they weren’t up there by the time of this post).
To leave a comment for the author, please follow the link and comment on their blog: Recology.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.