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Local Quantile Regression
- Publication Year :
- 2011
- Publisher :
- Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2011.
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Abstract
- Conditional quantile curves provide a comprehensive picture of a response contingent on explanatory variables. Quantile regression is a technique to estimate such curves. In a flexible modeling framework, a specific form of the quantile is not a priori fixed. Indeed, the majority of applications do not per se require specific functional forms. This motivates a local parametric rather than a global fixed model fitting approach. A nonparametric smoothing estimate of the conditional quantile curve requires to consider a balance between local curvature and variance. In this paper, we analyze a method based on a local model selection technique that provides an adaptive estimate. Theoretical properties on mimicking the oracle choice are offered and applications to stock market and weather analysis are presented.
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.od.......133..db67bf2f7ff09b91d1b7e2872d85167b