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Modeling Real Estate Data (German, Paperback)
Loot Price: R1,708
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Modeling Real Estate Data (German, Paperback)
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The statistical analysis of real estate data has received
increasingly more attention during the last decade. Property
owners, investors and banks are looking for cost-effective and
reliable means to assess the value of single properties or even
property portfolios. Additionally, building operating charges have
turned out to be a major determinant of profitability of real
estate investment, and the Europe-wide introduction of the energy
certification for buildings in 2002 enhances the importance of
accurate assessment of the energy efficiency of buildings even
more. The main purpose of this thesis is to apply approaches that
address nonlinearity and spatial or cluster-specific heterogeneity
simultaneously on real estate price and cost data. A particularly
broad and rich framework for semiparametric modeling is provided by
structured additive regression (STAR) models. In STAR-models,
continuous covariates are modeled as P(enalized)-splines.
Furthermore, possibly correlated discrete random effects for
spatial indexes, functions of two dimensional surfaces and
(spatially) varying coefficient terms may also be estimated using
this methodology.
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