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Survival analysis and Other Networks
Published in Basilio de Bragança Pereira, Calyampudi Radhakrishna Rao, Fábio Borges de Oliveira, Statistical Learning Using Neural Networks, 2020
Basilio de Bragança Pereira, Calyampudi Radhakrishna Rao, Fábio Borges de Oliveira
There are different types of censoring. Right censoring occurs if the events are not observed before the prespecified study-term or some competitive event (e.g., death by other cause) that causes interruption of the follow-up on the individual experimental unit.Left censoring happens if the starting point is located before the time of the beginning of the observation for the experimental unit (e.g., time of infection by HIV virus in a study of survival of AIDS patients).Interval censoring occurs if the exact time of an event is unknown, but we know that it falls within an interval Ii (e.g., when observations are grouped).
Predictive fidelity of bridge deterioration models: probabilistic vs deterministic
Published in Nigel Powers, Dan M. Frangopol, Riadh Al-Mahaidi, Colin Caprani, Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges, 2018
R. Goyal, M. Whelan, T. L. Cavalline
The most recent developments in probabilistic models are based on duration based analysis, which takes into account the aspect of time dependence of deterioration and also the impact of censoring (Mauch and Madanat 2001, Mishalani and Madanat 2002, Agrawal et al. 2010, Sobanjo 2011, Goyal 2015). ‘Censoring’ refers to instances of incomplete observation of an event, and is commonly encountered in duration data. Bridge condition rating data has a large number of censored observations, since discrete time measurements are made during the continuously ongoing deterioration process. Although accepted as superior, the suitability of duration based analysis is subject to the availability of at least 20 years length of inspection data. Since element level databases of most states are not developed for this duration, duration based studies have naturally relied on the original NBI database that offers several decades of consistently recorded condition rating data.
Some Probability Concepts for Engineers
Published in Richard L. Shell, Ernest L. Hall, Handbook of Industrial Automation, 2000
Censoring can be of two types: right censoring and left censoring. The above example is of the former type. An example of the latter type occurs when we measure say, pollution, using an instrument which cannot detect polution below a certain limit. In this case we have left censoring because only small values are censored. Of course, there are situations where both right and left censoring are present.
Impact of censoring types on the two-stage method for analyzing reliability experiments with random effects
Published in Quality Engineering, 2019
Shanshan Lv, Zhiqiong Wang, Zhen He, Geoffrey Vining
Reliability is one of the vital characteristics of products. Customers often make buying decisions based on the reliability of product. In order to meet the higher customer expectations for product reliability and to succeed in the competitive market, manufacturers are striving to improve their product lifetimes. However, measuring product lifetimes, even by accelerated testing conditions, often requires a great deal of time on test, which makes it impossible to collect all the lifetimes within a limited period under normal conditions. In many practical situations, some observational units may not fail given the constraint of time and cost of the experiment; thus, the data are usually censored, e.g., right, left, and interval censored. With the rapid development of technology, computers can help engineers to record the status of the product lifetime in real time. Instead of obtaining the interval censored data, engineers prefer to use right censoring scheme. Two widely used right censoring schemes are Type I censoring and Type II censoring. Type I censoring happens when the experiment stops at a predefined time. Type II censoring happens when the experiment stops at a predetermined failure numbers. Klein and Moeschberger (2003) and Nelson (2004) illustrated a detailed description of the censored data.
Condition prediction and estimation of service life in the presence of data censoring and dependent competing risks
Published in International Journal of Pavement Engineering, 2019
Valentin Donev, Markus Hoffmann
In this paper failure is defined as exceeding a given condition threshold triggering the application of maintenance and rehabilitation treatments. In general, condition thresholds differ among countries, agencies and road classes and have been set more or less arbitrarily (Hoffmann and Donev 2016). Figure 1 provides an overview of all common types of censoring in pavement management. If a road section has failed prior to a first survey, it is considered left censored, i.e. the true (latent) service life is less than the observed service life. Interval censoring occurs if the true lifetime is within a known interval of time (e.g. the survey interval Δt). If a pavement has not failed by the time of the last survey, it is considered right censored, i.e. the observed service life is less than the true service life.
Mixture of Birnbaum-Saunders Distributions: Identifiability, Estimation and Testing Homogeneity with Randomly Censored Data
Published in American Journal of Mathematical and Management Sciences, 2021
Walaa A. El-Sharkawy, Moshira A. Ismail
In the present paper, three fundamental problems are addressed for the mixture of BS distributions: First, the identifiability of a g-component without imposing a constraint on the shape parameter α, second, parameter estimation under random censoring using the EM algorithm, and third, testing the homogeneity of the mixture of BS distributions. To the best of our knowledge, no published work has been done on parametric estimation of the mixture of BS distributions under the censoring scheme. Censoring is an inevitable feature that arises in various fields such as clinical trials and reliability and life-testing experiments in the engineering sciences. It may occur naturally if the objects under study are lost from the test before failure or incorporated into the design of a study to save time and cost of the test. Various types of censoring schemes are based on the different termination techniques of life tests. The most common censoring schemes are Type I censoring, Type II censoring, and random censoring and they arise if the test ends at a fixed time, or with a fixed number of failures, or randomly according to certain criteria, respectively, as reported by Lawless (1982). The next significant problem in the applications of finite mixture models after the estimation problem is to decide whether the data comes from a homogenous (g = 1) or heterogeneous (g > 1) population. This problem is known as testing the number of components g or testing the order g of finite mixture models. In particular, in this paper, the EM test is proposed for testing homogeneity of the mixture of BS distributions. The effectiveness of the test is investigated through its size and power using a Monte Carlo simulation.