Suman Rakshit

Curtin University

5Publications

3H-index

22Citations

Publications 5

Newest

#1Suman Rakshit (Curtin University)H-Index: 3

#2Tilman M. Davies (University of Otago)H-Index: 9

Last.Adrian Baddeley (Curtin University)H-Index: 35

view all 7 authors...

#1Suman Rakshit (Curtin University)H-Index: 3

#2Adrian Baddeley (Curtin University)H-Index: 35

Last.Gopalan NairH-Index: 7

view all 3 authors...

We describe efficient algorithms and open-source code for the second-order statistical analysis of point events on a linear network. Typical summary statistics are adaptations of Ripley's K-function and the pair correlation function to the case of a linear network, with distance measured by the shortest path in the network. Simple implementations consume substantial time and memory. For an efficient implementation, the data structure representing the network must be economical in its use of memo...

#1Suman Rakshit (Curtin University)H-Index: 3

#2Gopalan Nair (UWA: University of Western Australia)H-Index: 7

Last.Adrian Baddeley (Curtin University)H-Index: 35

view all 3 authors...

Abstract The analysis of clustering and correlation between points on a linear network, such as traffic accident locations on a street network, depends crucially on how we measure the distance between points. Standard practice is to measure distance by the length of the shortest path. However, this may be inappropriate and even fallacious in some applications. Alternative distance metrics include Euclidean, least-cost, and resistance distances. This paper develops a general framework for the sec...

#1Adrian Baddeley (Curtin University)H-Index: 35

#2Andrew Hardegen (UWA: University of Western Australia)H-Index: 2

Last.Suman Rakshit (Curtin University)H-Index: 3

view all 6 authors...

A major weakness of the classical Monte Carlo test is that it is biased when the null hypothesis is composite. This problem persists even when the number of simulations tends to infinity. A standard remedy is to perform a double bootstrap test involving two stages of Monte Carlo simulation: under suitable conditions, this test is asymptotically exact for any fixed significance level. However, the two-stage test is shown to perform poorly in some common applications: for a given number of simulat...

#1Adrian Baddeley (Curtin University)H-Index: 35

#2Gopalan Nair (UWA: University of Western Australia)H-Index: 7

Last.Gregory Edward McSwiggan (UWA: University of Western Australia)H-Index: 2

view all 4 authors...

1