𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A new class of score generating functions for regression models

✍ Scribed by Young Hun Choi; Ömer Öztürk

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
127 KB
Volume
57
Category
Article
ISSN
0167-7152

No coin nor oath required. For personal study only.

✦ Synopsis

In this paper we introduce a new score generating function for the rank dispersion function in a multiple linear regression model. The score function compares the rth and sth power of the tail probabilities of the underlying probability model. We show that the rank estimator of the regression parameter based on the proposed score function converges asymptotically to a multivariate normal distribution. Further, we discuss the selection of the appropriate r and s to improve the e ciency of the rank estimate of the regression parameter. It is shown that for right-(left-) skewed distributions the values of r ¡ s (s ¡ r) provide higher e ciency than the Wilcoxon scores.

📜 SIMILAR VOLUMES

A New Class of Consistent Estimators for
A New Class of Consistent Estimators for Stochastic Linear Regressive Models
✍ Hong-Zhi An; Fred J Hickernell; Li-Xing Zhu 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 349 KB

In this paper we propose a new approach for estimating the unknown parameter in the stochastic linear regressive model with stationary ergodic sequence of covariates. Under mild conditions on the joint distribution of the covariate and the error, the estimator constructed is shown to be strongly con