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• W2953351570 abstract "Unconditional quantile regression (UQR) attracts attention in various fields to investigate the impacts of explanatory variables on quantiles of the marginal distribution of an explained variable. This study attempts to introduce spatial dependence into the UQR within the framework of random effects eigenvector spatial filtering, resulting in the model that we term the spatially filtered UQR (SF-UQR). We then develop a computationally efficient approach for SF-UQR estimation. Finally, the performance of the SF-UQR is tested with a hedonic land price model for the Tokyo metropolitan area. SF-UQR is implemented in an R package, spmoran." @default.
• W2953351570 created "2019-06-27" @default.
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• W2953351570 date "2017-06-23" @default.
• W2953351570 modified "2023-09-27" @default.
• W2953351570 title "Spatially filtered unconditional quantile regression: Application to a hedonic analysis" @default.
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• W2953351570 doi "https://doi.org/10.48550/arxiv.1706.07705" @default.
• W2953351570 hasPublicationYear "2017" @default.
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