Rigorous home range estimation with movement data: a new autocorrelated kernel density estimator

Rigorous home range estimation with movement data: a new autocorrelated kernel density estimator.

Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routi...

A Berry-Esseen Type Bound for the Kernel Density Estimator of Length-Biased Data

Length-biased data are widely seen in applications. They are mostly applicable in epidemiological studies or survival analysis in medical researches. Here we aim to propose a Berry-Esseen type bound for the kernel density estimator of this kind of data.The rate of normal convergence in the proposed Berry-Esseen type theorem is shown to be O(n^(-1/6) ) modulo logarithmic term as n tends to infin...

Asymptotic Behaviors of Nearest Neighbor Kernel Density Estimator in Left-truncated Data

Kernel density estimators are the basic tools for density estimation in non-parametric statistics.  The k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in  which  the  bandwidth  is varied depending on the location of the sample points. In this paper‎, we  initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...

A scaled line-based kernel density estimator for the retrieval of utilization distributions and home ranges from GPS movement tracks

Utilization distributions (UDs) can be used to describe with what intensity an animal or human may use a certain geographical location within the environment it is living in. Such a density distribution model represents one way to describe and obtain an animals’ home range in wildlife ecology. Several methods to derive UDs and subsequently home ranges have been developed, for instance Kernel De...

Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors