Minimax Regression Quantiles
A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question.
|Date of creation:||01 Aug 2010|
|Date of revision:|
|Contact details of provider:|| Web page: http://www.econ.au.dk/afn/|
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