A platform for research: civil engineering, architecture and urbanism
‘Truncate, replicate, sample’: A method for creating integer weights for spatial microsimulation
Highlights Integerisation of weights obtained from iterative proportional fitting. Evaluation of five methods for integerisation. New method presented, based on truncation, replication and sampling (TRS). The new method outperforms previously published integerisation strategies. Easily reproducible results, using publicly available R code and data.
Abstract Iterative proportional fitting (IPF) is a widely used method for spatial microsimulation. The technique results in non-integer weights for individual rows of data. This is problematic for certain applications and has led many researchers to favour combinatorial optimisation approaches such as simulated annealing. An alternative to this is ‘integerisation’ of IPF weights: the translation of the continuous weight variable into a discrete number of unique or ‘cloned’ individuals. We describe four existing methods of integerisation and present a new one. Our method – ‘truncate, replicate, sample’ (TRS) – recognises that IPF weights consist of both ‘replication weights’ and ‘conventional weights’, the effects of which need to be separated. The procedure consists of three steps: (1) separate replication and conventional weights by truncation; (2) replication of individuals with positive integer weights; and (3) probabilistic sampling. The results, which are reproducible using supplementary code and data published alongside this paper, show that TRS is fast, and more accurate than alternative approaches to integerisation.
‘Truncate, replicate, sample’: A method for creating integer weights for spatial microsimulation
Highlights Integerisation of weights obtained from iterative proportional fitting. Evaluation of five methods for integerisation. New method presented, based on truncation, replication and sampling (TRS). The new method outperforms previously published integerisation strategies. Easily reproducible results, using publicly available R code and data.
Abstract Iterative proportional fitting (IPF) is a widely used method for spatial microsimulation. The technique results in non-integer weights for individual rows of data. This is problematic for certain applications and has led many researchers to favour combinatorial optimisation approaches such as simulated annealing. An alternative to this is ‘integerisation’ of IPF weights: the translation of the continuous weight variable into a discrete number of unique or ‘cloned’ individuals. We describe four existing methods of integerisation and present a new one. Our method – ‘truncate, replicate, sample’ (TRS) – recognises that IPF weights consist of both ‘replication weights’ and ‘conventional weights’, the effects of which need to be separated. The procedure consists of three steps: (1) separate replication and conventional weights by truncation; (2) replication of individuals with positive integer weights; and (3) probabilistic sampling. The results, which are reproducible using supplementary code and data published alongside this paper, show that TRS is fast, and more accurate than alternative approaches to integerisation.
‘Truncate, replicate, sample’: A method for creating integer weights for spatial microsimulation
Lovelace, Robin (author) / Ballas, Dimitris (author)
Computers, Environments and Urban Systems ; 41 ; 1-11
2013-03-20
11 pages
Article (Journal)
Electronic Resource
English
‘Truncate, replicate, sample’: A method for creating integer weights for spatial microsimulation
Elsevier | 2013
|‘Truncate, replicate, sample’: A method for creating integer weights for spatial microsimulation
Online Contents | 2013
|A spatial microsimulation model with student agents
Online Contents | 2008
|A spatial microsimulation model with student agents
Online Contents | 2008
|