You are currently viewing an archived version of Topic Kernels and Density Estimation.
If updates or revisions have been published you can find them at Kernels and Density Estimation.
Learning Objectives:
Describe the relationships between kernels and classical spatial interaction approaches, such as surfaces of potential
Outline the likely effects on analysis results of variations in the kernel function used and the bandwidth adopted
Explain why and how density estimation transforms point data into a field representation
Explain why, in some cases, an adaptive bandwidth might be employed
Create density maps from point datasets using kernels and density estimation techniques using standard software
Differentiate between kernel density estimation and spatial interpolation
You are currently viewing an archived version of Topic Kernels and Density Estimation. If updates or revisions have been published you can find them at Kernels and Density Estimation.
Keywords: