Much operational reliability data available, e.g., in the nuclear industry, is heavily right-censored by preventive maintenance. The common methods for dealing with right-censored data (Total Time on Test statistic, Kaplan–Meier estimator, adjusted rank methods) assume the -independent competing-risk model for the underlying failure process and the censoring process, even though there are many ...

In this paper, we study a mixture model for survival data where covariates may innuence both the incidence probabilities and their conditional latency distributions. The data may include the exactly observed, the right-censored, and the interval-censored failure times. We apply the EM algorithm to nd the maximum likelihood estimate. We also carry out a Markov chain Monte Carlo algorithm for Bay...

The most of the results obtained about stochastic properties of generalized order statistics and their spacings in the literature are based on equal model parameters. In this paper, with less restrictive conditions on the model parameters, we prove some new multivariate likelihood ratio ordering results between two sub-vectors of GOS's as well as two sub-vectors of $p$-spacings based on two con...

In this paper we consider estimation of the derivative of a density based on wavelets methods using randomly right censored data. We extend the results regarding the asymptotic convergence rates due to Prakasa Rao (1996) and Chaubey et al. (2008) under random censorship model. Our treatment is facilitated by results of Stute (1995) and Li (2003) that enable us in demonstrating that the same con...

The self-consistent estimator is commonly used for estimating a survival function with interval-censored data. Recent studies on interval censoring have focused on case 2 interval censoring, which does not involve exact observations, and double censoring, which involves only exact, right-censored or left-censored observations. In this paper, we consider an interval censoring scheme that involve...

In this thesis, we develop the necessary statistical framework to produce accurate forecasts of total bookings in a particular fare class on a specific flight number departing on a given date at various points before departure. After an introduction to the basic terminology of the airline booking process, a rigorous probabilistic model is developed. The booking process is modeled as a stochasti...