New Dispersion Function in the Rank Regression

Title & Authors
New Dispersion Function in the Rank Regression
Choi, Young-Hun;

Abstract
In this paper we introduce a new score generating (unction for the rank regression in the linear regression model. The score function compares the $\small{\gamma}$'th and s\`th power of the tail probabilities of the underlying probability distribution. We show that the rank estimate asymptotically converges to a multivariate normal. further we derive the asymptotic Pitman relative efficiencies and the most efficient values of $\small{\gamma}$ and s under the symmetric distribution such as uniform, normal, cauchy and double exponential distributions and the asymmetric distribution such as exponential and lognormal distributions respectively
Keywords
Score;Rank estimate;Regression;Asymptotic normality;Efficiency;
Language
English
Cited by
1.
Hypothesis Testing for New Scores in a Linear Model,;

Communications for Statistical Applications and Methods, 2003. vol.10. 3, pp.1007-1015
1.
Hypothesis Testing for New Scores in a Linear Model, Communications for Statistical Applications and Methods, 2003, 10, 3, 1007
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