Open Science Research Excellence
%0 Journal Article
%A Yan Wang and  Yasushi Asami and  Yukio Sadahiro
%D 2015 
%J  International Journal of Civil, Environmental, Structural, Construction and Architectural Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 100, 2015
%T A Research on Inference from Multiple Distance Variables in Hedonic Regression – Focus on Three Variables
%U http://waset.org/publications/10001092
%V 100
%X In urban context, urban nodes such as amenity or
hazard will certainly affect house price, while classic hedonic analysis
will employ distance variables measured from each urban nodes.
However, effects from distances to facilities on house prices generally
do not represent the true price of the property. Distance variables
measured on the same surface are suffering a problem called
multicollinearity, which is usually presented as magnitude variance
and mean value in regression, errors caused by instability. In this paper,
we provided a theoretical framework to identify and gather the data
with less bias, and also provided specific sampling method on locating
the sample region to avoid the spatial multicollinerity problem in three
distance variable’s case.

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