Ordinary Least Squares for Histogram Data Based on Wasserstein Distance

Rosanna Verde () and Antonio Irpino ()
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Rosanna Verde: Seconda Universitá degli Studi di Napoli, Dipartimento di Studi Europei e Mediterranei
Antonio Irpino: Seconda Universitá degli Studi di Napoli, Dipartimento di Studi Europei e Mediterranei

A chapter in Proceedings of COMPSTAT'2010, 2010, pp 581-588 from Springer

Abstract: Abstract Histogram data is a kind of symbolic representation which allows to describe an individual by an empirical frequency distribution. In this paper we introduce a linear regression model for histogram variables. We present a new Ordinary Least Squares approach for a linear model estimation, using the Wasserstein metric between histograms. In this paper we suppose that the regression coefficient are scalar values. After having illustrated the concurrent approaches, we corroborate the proposed estimation method by an application on a real dataset.

Keywords: probability distribution function; histogram data; ordinary least squares; Wasserstein distance (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2604-3_60

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DOI: 10.1007/978-3-7908-2604-3_60

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