📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Kernel density estimation for undirected dyadic data (2019)

First Author: Powell J

Attributed to: Advancing Microdata Models and Methods funded by ESRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1920/wp.cem.2019.3919

Publication URI: http://dx.doi.org/10.1920/wp.cem.2019.3919

Type: Working Paper