Extension of multivariate regression trees to interval data. Application to elasticity load profiling
type: Item
instance of: scholarly article
title: Extension of multivariate regression trees to interval data. Application to elasticity load profiling
zbMATH Open document ID: 1113.62046
author: Véronique Cariou
published in: Computational Statistics
publication date: 2007-05-29T00:00:00Z
review text: A regression tree growing algorithm is considered for data with multivariate interval-valued response and quantitative or nominal predictors. The splitting function is based on the Hausdorff metrics for intervals and least absolute deviations distance. The symbolic object principal component analysis procedure is recommended as a pre-processing algorithm. The developed technique is applied to the data on French customers electricity loading patterns.
Mathematics Subject Classification ID: 62G08
Mathematics Subject Classification ID: 62H25
Mathematics Subject Classification ID: 62P30
Mathematics Subject Classification ID: 62J02
zbMATH DE Number: 5158603
zbMATH Keywords: symbolic data analysis
zbMATH Keywords: Hausdorff metrics
zbMATH Keywords: least absolute deviations
describes a project that uses: SODAS
MaRDI profile type: Publication
full work available at URL: s00180-006-0266-7
OpenAlex ID: W2087177152
cites work: Analysis of symbolic data. Exploratory methods for extracting statistical information from complex data
cites work: Q3327527
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DOI: 10.1007/S00180-006-0266-7
description: scientific article; zbMATH DE number 5158603