Linear and Nonparametric Quantile Regression

Daniel McMillen ()

Chapter Chapter 2 in Quantile Regression for Spatial Data, 2013, pp 13-27 from Springer

Abstract: Abstract Quantile regression estimates can be presented in tables alongside linear regression estimates. A possible advantage of this approach to presenting quantile regression results is that it is easy to compare the values of the coefficients and standard errors with OLS estimates and across quantiles. As we have seen, quantile estimates actually contain far more information than can be presented in simple tables. The estimates imply a full distribution of values for the dependent variable. It also is easy to show how changes in the explanatory variables affect the distribution of the dependent variable.

Keywords: Quantile Regression; Single Explanatory Variable; Kernel Weighting Function; Chosen Target Point; Base Regression Line (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-3-642-31815-3_2

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