A note on construction of heuristically optimal Pena’s synthetic indicators by the particle swarm method of global optimization
Pena’s method of construction of a synthetic indicator is very sensitive to the order in which the constituent variables (whose linear aggregation yields the synthetic indicator) are arranged. Due to this, Pena’s method can at present give only an arbitrary synthetic indicator whose representativeness is indeterminate and uncertain, especially when the number of constituent variables is not very small. This paper uses discrete global optimization method based on the Particle Swarms to obtain a heuristically optimal order in which the constituent variables can be arranged so as to yield Pena’s synthetic indicator that maximizes the minimal absolute (or squared) correlation with its constituent variables.
|Date of creation:||24 Mar 2012|
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- José-María Montero & Coro Chasco & Beatriz Larraz, 2010. "Building an environmental quality index for a big city: a spatial interpolation approach combined with a distance indicator," Journal of Geographical Systems, Springer, vol. 12(4), pages 435-459, December.
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- Mishra, SK, 2007. "A Note on Human Development Indices with Income Equalities," MPRA Paper 3513, University Library of Munich, Germany.
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- Mishra, SK, 2006. "Performance of Differential Evolution and Particle Swarm Methods on Some Relatively Harder Multi-modal Benchmark Functions," MPRA Paper 449, University Library of Munich, Germany.
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