Sparse Methods for Analysis of Sparse Multivariate Data From Big Economic Databases

Jerzy Rydlewski, Malgorzata Snarska, Dominik Mielczarek () and Daniel Kosiorowski ()

Statistics in Transition new series, 2014, vol. 15, issue 1, 111-132

Abstract: In this paper we present a novel perspective dedicated for sparse highdimensional data sets, i.e. data which contain many zeros among coordinates of observations. Using jointly, selected sparse methods recently proposed in multivariate statistics, and kernel density framework for discrete data, we outline a general perspective for bringing out useful information from big economic databases. As a framework for our considerations we take the so-called functional data analysis, which originates from Ramsay and Silverman works. In particular we use functional principal components analysis within 2D density estimation procedure proposed by Simonoff.

Keywords: sparse data; sparse methods; robust methods; categorical data; big data (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:csb:stintr:v:15:y:2014:i:1:p:111-132

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