A kernel nonparametric quantile estimator for right-censored competing risks data

In medical and epidemiological studies, it is often interest to study time-to-event distributions under competing risks that involve two or more failure types. Nonparametric analysis of competing risks is typically focused on the cumulative incidence function or nonparametric quantile function. Howe...

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Veröffentlicht in:	Journal of applied statistics 2020-01, Vol.47 (1), p.61-75
Hauptverfasser:	Fan, Caiyun, Ding, Gang, Zhang, Feipeng
Format:	Artikel
Sprache:	eng
Schlagworte:	Bahadur representation Competing risks Confidence intervals Economic models Epidemiology Failure analysis Kernels Monte Carlo simulation Nonparametric statistics quantile right censored Statistical methods weak convergence
Online-Zugang:	Volltext
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