The aim of regression clustering (Bin Zhang, 2003) is segmenting a number of units in some clusters in order to detect a good regression model in each cluster. Then regression clustering is suitable when, given some explicative variables (regressors), a single regression model doesn’t fit well all the units, but different regression models might fit well partitions of the data (see also Sarstedt and Schwaiger (2006)). In this paper a regression clustering procedure is adapted to a particular regression to predict the pro capita disposal income (PCDI) in municipalities. The particularity of this regression consist in: it is a two-level regression (municipalities and provinces) and the parameters estimation is run at the provincial level under some assumptions.

A regression clustering method for the prediction of the pro capita disposal income in municipalities

CHIRICO, PAOLO
2010-01-01

Abstract

The aim of regression clustering (Bin Zhang, 2003) is segmenting a number of units in some clusters in order to detect a good regression model in each cluster. Then regression clustering is suitable when, given some explicative variables (regressors), a single regression model doesn’t fit well all the units, but different regression models might fit well partitions of the data (see also Sarstedt and Schwaiger (2006)). In this paper a regression clustering procedure is adapted to a particular regression to predict the pro capita disposal income (PCDI) in municipalities. The particularity of this regression consist in: it is a two-level regression (municipalities and provinces) and the parameters estimation is run at the provincial level under some assumptions.
2010
GfKl - CLADAG 2010
Firenze
8-10 Settembre 2010
GfKl - CLADAG 2010 Book of Abstracts
CLADAG 2010
1
135
136
Regression clustering; pro capita disposal income
CHIRICO P.
File in questo prodotto:
File Dimensione Formato  
2010 Cladag Firenze.pdf

Accesso riservato

Tipo di file: PDF EDITORIALE
Dimensione 179.45 kB
Formato Adobe PDF
179.45 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/82695
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact