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License: CC BY NC ND
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Data wrangling, computational burden, automation, robustness and accuracy in ecological inference forecasting of R×C tables

Authors: Pavía, Jose M.; Romero, Rafael;

Data wrangling, computational burden, automation, robustness and accuracy in ecological inference forecasting of R×C tables

Abstract

This paper assesses the two current major alternatives for ecological inference, based on a multinomial-Dirichlet Bayesian model and on mathematical programming. Their performance is evaluated in a database made up of almost 2000 real datasets for which the actual cross-distributions are known. The analysis reveals both approaches as complementarity, each one of them performing better in a different area of the simplex space, although with Bayesian solutions deteriorating when the amount of information is scarce. After offering some guidelines regarding the appropriate contexts for employing each one of the algorithms, we conclude with some ideas for exploiting their complementarities.

Peer Reviewed

Keywords

Combinatorial analysis, ei.MD.bayes, 05 Combinatòria, Classificació AMS::05 Combinatorics::05A Enumerative combinatorics, mathematical programming::90C Mathematical programming, two-way contingency tables, Ei.MD.bayes, lphom, Classificació AMS::91 Game theory, economics, social and behavioral sciences, ecologia, Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, voter transitions, Two-way contingency tables, R-packages, Game theory, ecological inference, 05A Problemes de combinatòria clàssica, Classificació AMS::90 Operations research, 90C Programació matemàtica, US voting rights, Programming (Mathematics), social and behavioral sciences, bancs de dades, Classificació AMS::91 Game theory, Lphom, economics, Classificació AMS::90 Operations research, mathematical programming::90C Mathematical programming, Classificació AMS::05 Combinatorics, Ecological inference, automatització, 91A Teoria de jocs, Voter transitions, dades transmissió

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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