Nonparametric Estimation and Inference for Reliability

A nonparametric procedure for both point and interval estimation of percentiles, hazard rate, cummulative hazard and survival function is developed. The procedure is based upon the assumption that a time to failure random variable can be closely approximated by a polynomial in an exponential random variable. Accuracy of the approximation is demonstrated. Monte Carlo s-confidence bounds are derived for the estimated functions. Within the range of observed data, the estimated functions are useful for computations such as cost optimization of maintenance and replacement policies.