On the complexity of optimally modifying graphs representing spatial correlation in areal unit count data

10/20/2020
by   Duncan Lee, et al.
0

Lee and Meeks recently demonstrated that improved inference for areal unit count data can be achieved by carrying out modifications to a graph representing spatial correlations; specifically, they delete edges of the planar graph derived from border-sharing between geographic regions in order to maximise a specific objective function. In this paper we address the computational complexity of the associated graph optimisation problem, demonstrating that it cannot be solved in polynomial time unless P = NP.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/21/2020

Improved inference for areal unit count data using graph-based optimisation

Spatial correlation in areal unit count data is typically modelled by a ...
research
10/08/2022

APUD(1,1) Recognition in Polynomial Time

A unit disk graph is the intersection graph of a set of disk of unit rad...
research
12/17/2020

Maximum cut on interval graphs of interval count four is NP-complete

The computational complexity of the MaxCut problem restricted to interva...
research
01/31/2023

p-median location interdiction on trees

In p-median location interdiction the aim is to find a subset of edges i...
research
06/28/2021

Representing polynomial of CONNECTIVITY

We show that the coefficients of the representing polynomial of any mono...
research
02/06/2020

On flips in planar matchings

In this paper we investigate the structure of a flip graph on non-crossi...
research
09/06/2023

Adaptive Sampling of 3D Spatial Correlations for Focus+Context Visualization

Visualizing spatial structures in 3D ensembles is challenging due to the...

Please sign up or login with your details

Forgot password? Click here to reset