Maximum Likelihood Analysis of Circular Data


A series of wrapper functions to implement the 10 maximum likelihood models of animal orientation described by Schnute and Groot (1992) doi: 10.1016/S0003-3472(05)80068-5. The functions also include the ability to use different optimizer methods and calculate various model selection metrics (i.e., AIC, AICc, BIC). This framework is designed for modeling any dataset represented by angles (e.g, orientation, periodic, etc) using the above models. Main features are listed as follows.

Install CircMLE (from an R console)

Version History


Fitak, R. R. and Johnsen, S. (2017) Bringing the analysis of animal orientation data full circle: model-based approaches with maximum likelihood. Journal of Experimental Biology 220: 3878-3882; doi: 10.1242/jeb.167056

If using the Hermans-Rasson or Pycke tests then cite:
Landler, L., Ruxton, G. D., and Malkemper, E. P. (2019) The Hermans–Rasson test as a powerful alternative to the Rayleigh test for circular statistics in biology. BMC Ecology 19: 30; doi: 10.1186/s12898-019-0246-8


Robert Fitak
Department of Biology
University of Central Florida