Estimation of the pair correlation function
Date:
The pair correlation function is a key summary statistic in analyzing spatial point patterns. It has become an important tool in forestry, cosmology and other disciplines. Kernel smoothing methods are often used to estimate the pair correlation function, similar to kernel estimation of probability densities. However, the kernel estimator with symmetric bounded support kernels suffers from the well-known boundary bias problem and the bias and variance of a kernel estimate depend critically on the choice of kernel bandwidth. In the present research project, we aim to use asymmetric kernel functions in order to eliminate the boundary bias issue and develop a feasible methodology for optimal choice of the bandwidth.