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A modified kernel quantile estimator under censoring
Author(s) -
Lio Y. L.,
Padgett W. J.
Publication year - 1988
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3314638
Subject(s) - censoring (clinical trials) , quantile , mathematics , estimator , statistics , kernel smoother , kernel (algebra) , econometrics , computer science , kernel method , artificial intelligence , combinatorics , radial basis function kernel , support vector machine
Based on right‐censored data from a lifetime distribution F 0 , a modification of the kernel quantile estimator is proposed. The advantage of this estimator is that the data play a role in the degree of smoothing of the estimator while retaining the desirable features of the kernel estimator. Convergence in probability and almost sure convergence of the estimator are discussed. Also, asymptotic normality and confidence bands are presented and some examples are given.