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We discuss inference for additive models with random scaling factors. The additive effects are of the form (1+g)f(z) where f is a nonlinear function of the continuous covariate z modeled by P(enalized)-splines and 1+g is a random scaling factor. Additionally, monotonicity constraints on the...
Persistent link: https://www.econbiz.de/10005232756
We apply additive mixed regression models (AMM) to estimate hedonic price equations. Non-linear effects of continuous covariates as well as a smooth time trend are modeled non-parametrically through P-splines. Unobserved district-specific heterogeneity is modeled in two ways: First, by location...
Persistent link: https://www.econbiz.de/10005427649
Models with structured additive predictor provide a very broad and rich framework for complex regression modeling. They can deal simultaneously with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity and complex interactions between...
Persistent link: https://www.econbiz.de/10010547919
Based on more than 10.000 observations of rental flats in Vienna, collected from 2004 to 2006, we apply Bayesian structured additive regression models to estimate hedonic price equations. For this purpose we use explanatory variables such as the buildingís year of construction, its total floor...
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SUMMARY Semiparametric quantile regression is employed to flexibly estimate sales response for frequently purchased consumer goods. Using retail store‐level data, we compare the performance of models with and without monotonic smoothing for fit and prediction accuracy. We find that (a)...
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