作者: V. N. NAIR
关键词: Nonparametric statistics 、 Probability plot 、 Cumulative hazard 、 Quantile 、 Censoring (statistics) 、 Mathematics 、 Econometrics 、 Survival function 、 Goodness of fit 、 Statistics
摘要: SUMMARY In this paper, we consider nonparametric procedures for assessing goodness of fit when the data may be subject to random censoring. We introduce two classes large-sample tests, based, respectively, on maximum and average weighted difference between specified survival function Kaplan-Meier estimate true function. The in first class are inverted obtain simultaneous confidence bands cumulative hazard functions. These provide associated with percentage (P-P), quantile (Q-Q) plots censored data. Some key word8: Hazard function; Nonparametric procedure; Probability plot; Shift Survival