ctmm-package: Continuous-time movement modeling
Description
Description: Functions for identifying, fitting, and applying continuous-space, continuous-time stochastic movement models to animal tracking data.
The methods are based on those introduced in Fleming et al. (2014-2015).Details
ll{
Package: ctmm
Type: Package
Version: 0.3.1
Date: 2015-02-23
License: GPL-3
}References
C. H. Fleming, J. M. Calabrese, T. Mueller, K.A. Olson, P. Leimgruber, and W. F. Fagan. (2014).
From fine-scale foraging to home ranges: A semi-variance approach to identifying movement modes across spatiotemporal scales.
http://www.jstor.org/discover/10.1086/675504{The American Naturalist, 183(5), E154-E167}.
C. H. Fleming and J. M. Calabrese and T. Mueller and K. A. Olson and P. Leimgruber, and W. F. Fagan (2014).
Non-Markovian maximum likelihood estimation of autocorrelated movement processes
http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12176/abstract{Methods in Ecology and Evolution, 5(5) 462-472}.
C. H. Fleming and Y. Subasi and J. M. Calabrese. (2015).
A maximum-entropy description of animal movement.
http://journals.aps.org/pre/abstract/10.1103/PhysRevE.91.032107{Physical Review E, 91, 032107}.
C. H. Fleming and W. F. Fagan and T. Mueller and K. A. Olson and P. Leimgruber, and J. M. Calabrese (2015).
Rigorous home-range estimation with movement data: A new autocorrelated kernel-density estimator.
http://www.esajournals.org/doi/abs/10.1890/14-2010.1{Ecology, 96(5), 1182-1188}.
C. H. Fleming, W. F. Fagan, T. Mueller, K. A. Olson, P. Leimgruber, and J. M. Calabrese. (2016).
Estimating where and how animals travel: An optimal framework for path reconstruction from autocorrelated tracking data.
http://onlinelibrary.wiley.com/doi/10.1890/15-1607/full{Ecology 10.1890/15-1607}.