An evaluation of the combinatorial optimisation approach to the creation of synthetic microdata

The Challenges of Combining Two Databases in Small-Area Estimation: An Example Using Spatial Microsimulation of Child Poverty

“…In SpatialMSM, 'error' is measured by the total absolute error (TAE) from all the benchmarks. The TAE has been used in a number of spatial microsimulation models as a criterion for reweighting accuracy (Anderson, 2007;Williamson et al, 1998) and has been assessed and supported by the results of other studies, such as Smith et al (2009) and Voas and Williamson (2000).…”

The Challenges of Combining Two Databases in Small-Area Estimation: An Example Using Spatial Microsimulation of Child Poverty

“…In SpatialMSM, 'error' is measured by the total absolute error (TAE) from all the benchmarks. The TAE has been used in a number of spatial microsimulation models as a criterion for reweighting accuracy (Anderson, 2007;Williamson et al, 1998) and has been assessed and supported by the results of other studies, such as Smith et al (2009) and Voas and Williamson (2000).…”

Getting the best of both worlds: a framework for combining disaggregate travel survey data and aggregate mobile phone data for trip generation modelling

“…Another popular technique is combinatorial optimisation, which focusses on selecting a subset of households in the disaggregate sample data that closely fit the marginal distributions in the census data for the same area (Voas and Williamson 2000). This is done by randomly selecting an initial subset of households from the sample data, and iteratively replacing these with those remaining in the sample data, if and only when this leads to improvements in the fit of the subset.…”

Estimating small-area Indigenous cultural participation from synthetic survey data

“…Other spatial microsimulation methods that use a reweighting technique have used a probabilistic method that pseudo-randomly selects households to fill an area (Voas and Williamson, 2000;Williamson et al, 1998). This method has the advantage of retaining estimates for all the areas while the GREGWT algorithm sometimes fails to calculate an estimate.…”

“…where X cp is the actual estimate for each benchmark p from the sensus, X ap is the modelled estimate for each benchmark, and Pop z is the population in small area z. The TAE has been used in a number of spatial microsimulation models as a criterion for reweighting accuracy (Anderson, 2007;Williamson et al, 1998) and has been assessed and supported by other studies, such as Smith et al (2009) and Voas and Williamson (2000).…”

The Challenges of Combining Two Databases in Small-Area Estimation: An Example Using Spatial Microsimulation of Child Poverty

“…In SpatialMSM, 'error' is measured by the total absolute error (TAE) from all the benchmarks. The TAE has been used in a number of spatial microsimulation models as a criterion for reweighting accuracy (Anderson, 2007;Williamson et al, 1998) and has been assessed and supported by the results of other studies, such as Smith et al (2009) and Voas and Williamson (2000).…”

Getting the best of both worlds: a framework for combining disaggregate travel survey data and aggregate mobile phone data for trip generation modelling

“…Another popular technique is combinatorial optimisation, which focusses on selecting a subset of households in the disaggregate sample data that closely fit the marginal distributions in the census data for the same area (Voas and Williamson 2000). This is done by randomly selecting an initial subset of households from the sample data, and iteratively replacing these with those remaining in the sample data, if and only when this leads to improvements in the fit of the subset.…”

Estimating small-area Indigenous cultural participation from synthetic survey data

“…Other spatial microsimulation methods that use a reweighting technique have used a probabilistic method that pseudo-randomly selects households to fill an area (Voas and Williamson, 2000;Williamson et al, 1998). This method has the advantage of retaining estimates for all the areas while the GREGWT algorithm sometimes fails to calculate an estimate.…”

“…where X cp is the actual estimate for each benchmark p from the sensus, X ap is the modelled estimate for each benchmark, and Pop z is the population in small area z. The TAE has been used in a number of spatial microsimulation models as a criterion for reweighting accuracy (Anderson, 2007;Williamson et al, 1998) and has been assessed and supported by other studies, such as Smith et al (2009) and Voas and Williamson (2000).…”

The Challenges of Combining Two Databases in Small-Area Estimation: An Example Using Spatial Microsimulation of Child Poverty

“…In SpatialMSM, 'error' is measured by the total absolute error (TAE) from all the benchmarks. The TAE has been used in a number of spatial microsimulation models as a criterion for reweighting accuracy (Anderson, 2007;Williamson et al, 1998) and has been assessed and supported by the results of other studies, such as Smith et al (2009) and Voas and Williamson (2000).…”

Getting the best of both worlds: a framework for combining disaggregate travel survey data and aggregate mobile phone data for trip generation modelling

“…Another popular technique is combinatorial optimisation, which focusses on selecting a subset of households in the disaggregate sample data that closely fit the marginal distributions in the census data for the same area (Voas and Williamson 2000). This is done by randomly selecting an initial subset of households from the sample data, and iteratively replacing these with those remaining in the sample data, if and only when this leads to improvements in the fit of the subset.…”

Estimating small-area Indigenous cultural participation from synthetic survey data

“…Other spatial microsimulation methods that use a reweighting technique have used a probabilistic method that pseudo-randomly selects households to fill an area (Voas and Williamson, 2000;Williamson et al, 1998). This method has the advantage of retaining estimates for all the areas while the GREGWT algorithm sometimes fails to calculate an estimate.…”

“…where X cp is the actual estimate for each benchmark p from the sensus, X ap is the modelled estimate for each benchmark, and Pop z is the population in small area z. The TAE has been used in a number of spatial microsimulation models as a criterion for reweighting accuracy (Anderson, 2007;Williamson et al, 1998) and has been assessed and supported by other studies, such as Smith et al (2009) and Voas and Williamson (2000).…”