2015. "Conditionally Parametric Quantile Regression for Spatial Data: An Analysis of Land Values in Early Nineteenth Century Chicago," Regional Science and Urban Economics, 55, 28-38.McMillen, Daniel P., "Condi
Cite this chapter McMillen, D.P. (2013). Quantile Regression: An Overview. In: Quantile Regression for Spatial Data. SpringerBriefs in Regional Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31815-3_1 Download citation .RIS .ENW .BIB DOIhttps://doi.org/10.1007/...
Classical least squares regression may be viewed as a natural way of extending the idea of estimating an unconditional mean parameter to the problem of estimating conditional mean functions ; the crucial link is the formulation of an optimization problem that encompasses both problems. Likewise, quant...
This study employs quantile regression, load capacity curves, and DKSE to investigate the relationships between environmental sustainability and factors such as forestry, financial integration, population growth, economic growth, and urbanization in BIMSTEC zone. It utilizes recent data to evaluate the ...
S. CADE (2000): "Paradigm Shift in Theory and Methods: Regression Quantile Analysis Enables New Insights for Ecology," in Proceedings of the 4th International Conference on Integrating Geographic Information Systems and Environmental Modeling: Problems, Prospects, and Needs for Research, ed. ...
(2008) apply a novel spatial quantile regression and use the data of Orem-Provo, Utah, United States. They discover that some housing attributes are valued quite differently across the conditional price distribution. However, they observe negligible spatial dependence and conclude that quantile effects...
Quantile Regression for Spatial Data.pdf A Lack-of-Fit Test for Quantile Regression Composite quantile regression and the oracle model selection theory nullComposite Quantile Regression and The Oracle Model Selection Theory Tax Incentives and Charitable Contributions the Evidence from Censored Quantile Regres...
This work examines the changes in daily mean air temperature over Central Europe using quantile regression, which allows the estimation of trends, not only in the mean but in all parts of the data distribution. A bootstrap procedure is applied for assessing uncertainty on the derived slopes and...
Quantile regression forest (QRF) was used for the spatial assessment of the ECe using R quantreg (ranger package); this approach can provide the probability distribution estimated of the prediction (Meinshausen, 2006) (and related uncertainty expressed as per quantiles; Lombardo et al., 2018). ...
D-vine Copula quantile regression COVID-19 Italian data Spatial dependence 1. Introduction In the late December 2019, the atypical pneumonia originated by SARSCoV-2 virus has exponentially spread out from the city of Wuhan, the capital of the Chinese province of Hubei, identified as the epicentre...