Nonparametric estimate based on imputations techniques for interval and partly interval censored data

This paper discusses the nonparametric analysis of interval and partly interval censored data, which is occur in many fields including demographical, epidemiological, financial, medical and sociological studies. For Partly Interval Censored (PIC) we mean that for some subjects the exact failure time is observed while the rest are only known to fall within an interval (Kim 2003). In medical and reliability studies the most important function is the survival function. However, we used a nonparametric model to estimate the survival function based on different imputation techniques in the present of interval censored and PIC data. Our proposal is easily implemented using R software