CircMLE
Maximum Likelihood Analysis of Circular Data
Description
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.
- Calculate the likelihood of any one or all of the 10 models of
orientation
- Compare any two nested models using a likelihood ratio test
- Plot the observed dataset and any of the model-fitted results
- Calculate the Hermans-Rasson test or Pycke test for
directionality
Install CircMLE (from an R
console)
- To install from CRAN
- First install the R package ‘circular’ from CRAN using the command
install.packages("circular")
- Then install the CircMLE package using
install.packages("CircMLE")
- Load the package into your working R environment using
library(CircMLE)
Version History
- Version 3.0.0 2020/2/9
- Added the circular distance correlation function. Thanks Matt
Robinson for the great ideas and discussion!
- the model fitting function now includes the hessian matrix, and a
function ci_circmle to calculate 95% confidence intervals for the MLE
parameters.
- Thanks Oliver Mitesser (University of Wörzburg) for the
recommendation!
- Version 0.2.3 2020/1/29
- Added the ability to perform the Hermans-Rasson and Pycke tests
using code kindly provided by Lukas Landler, Graeme Ruxton, and E.
Pascal Malkemper.
- Version 0.2.2 2019/10/17
- Improved communication between CircMLE and R ‘circular’
objects, especially for improved plotting when using ‘template =
“geographics”’.
- Version 0.2.1 2018/02/20
- Added support for data vectors with the “geographics” template set
when plotting the modeled results.
- Added publication information
- Added the README.md file
- Version 0.2.0 2017/06/29
- Added a plotting function to visualize the observed and modeled
results
- Version 0.1, 2017/05/13
- Released the first version
Citation
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
- Or enter the command
citation("CircMLE")
into your R
console
Robert Fitak
Department of Biology
University of Central Florida
USA
rfitak9@gmail.com