Characterization of Home Range Using Point Peeling.
The home range is the area “traversed by an individual (animal) in its normal activities of food gathering, mating and caring for young” (Burt 1943:351), whereas the utilization distribution reflects the animal's spatial use probability density (Van Winkle 1975, Signer et al. 2017). Recently, the home range has been viewed as one attribute of the animal's utilization distribution.
Density estimation in R Henry Deng and Hadley Wickham September 2011 Abstract Density estimation is an important statistical tool, and within R there are over 20 packages that implement it: so many that it is often di cult to know which to use. This paper presents a brief outline of the theory underlying each package, as well as an.
Recent literature has reported inaccuracies associated with some popular home range estimators such as kernel density estimation, especially when applied to point patterns of complex shapes. This study explores the use of characteristic hull polygons (CHPs) as a new method of home range estimation. CHPs are special bounding polygons created in GIS that can have concave edges, be composed of.
Downloadable! An asymptotic theory is developed for the kernel density estimate of a random walk and the kernel regression estimator of a nonstationary first order autoregression. The kernel density estimator provides a consistent estimate of the local time spent by the random walk in the spatial vicinity of a point that is determined in part by the argument of the density and in part by.
Home range estimator options included in the software but not recommended by the authors: Harmonic Mean Home Range “Placed here mainly for the purpose of examining activity centers and for obtaining habitat relationships based on a gridded distance measurements” (Hooge 2000) Jennrich-Turner Bivariate Normal Home Range.
A genetic algorithm for spatiotemporal cluster detection and analysis D.Dai and T.J.Oyana: Employing agents to develop integrated urban models - numerical results from residential mobility experiments O.Devisch, T.Arentze, A.Borgers and H.Timmermans: Network-Based Kernel Density Estimation for Home Range Analysis J.A. Downs and M.W. Horner.
Dividing the number of weaned individuals by home range size based on direct observations resulted in a density of 1.25 individuals per km 2 (hereafter referred to as “known density”). In order to obtain a density estimate for the Rekambo community, we ran the same SECR models as described above but with a subset of the data.