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Friedman, J.H. and Fisher, N.I. (1999) Bump Hunting in High-Dimensional Data. Statistics and Computing, 9, 123-143.
http://dx.doi.org/10.1023/A:1008894516817

has been cited by the following article:

• TITLE: Empirical Likelihood Diagnosis of Modal Linear Regression Models

  AUTHORS: Shuling Wang, Lin Zheng, Jiangtao Dai

  KEYWORDS: Modal Linear Regression Model, Empirical Likelihood, Outliers, Influence Analysis

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.2 No.10, September 30, 2014

  ABSTRACT: In this paper, we investigate the empirical likelihood diagnosis of modal linear regression models. The empirical likelihood ratio function based on modal regression estimation method for the regression coefficient is introduced. First, the estimation equation based on empirical likelihood method is established. Then, some diagnostic statistics are proposed. At last, we also examine the performance of proposed method for finite sample sizes through simulation study.