Quantile Regression: An Overview

Daniel McMillen ()

Chapter Chapter 1 in Quantile Regression for Spatial Data, 2013, pp 1-11 from Springer

Abstract: Abstract Linear regression is the standard tool for empirical studies in most of the social sciences. When the relationship between a dependent variable, y, and a set of explanatory variables, X, can be written as $$ y = X\beta + u $$ , a simple ordinary least squares (OLS) regression of y on X can potentially provide unbiased estimates of the parameters, β, and a predicted value, $$ \widehat{y} = X\widehat{\beta } $$ is the best guess of the value of y given values for X. A glance at any journal in the social sciences quickly reveals the dominance of regression analysis as the tool for empirical analysis.

Keywords: Ordinary Little Square; House Price; Quantile Regression; Ordinary Little Square Regression; Sale Price (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/978-3-642-31815-3_1

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