Estimation in interval censored data

Download

index.pdf

Date

2014

Author

Bayramoğlu, Könül

Metadata

Show full item record

Item Usage Stats

124
views

109
downloads

Interval censored failure time data occur in many areas including medicine, economics, zoology, psychology, sociology and engineering. In such studies, the variable of interest is often not exactly observed, but known to fall within some interval. In this thesis, the likelihood functions for fixed and random interval censored data are obtained. Modified Maximum Likelihood and Copula Methods are utilized for the estimation of unknown parameters. Bivariate interval censored data are also considered as a generalization in this work. To estimate the association between two random variables, we focus on the situation where they follow a copula model. To check the accuracy and efficiency of the methods, some numerical studies are conducted.

Subject Keywords

Censored observations (Statistics)., Distribution (Probability theory)., Sampling (Statistics)., Random data (Statistics)., Estimation theory.

URI

http://etd.lib.metu.edu.tr/upload/12617512/index.pdf
https://hdl.handle.net/11511/23670

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Estimation and hypothesis testing in multivariate linear regression models under non normality İslam, Muhammed Qamarul (Informa UK Limited, 2017-01-01) This paper discusses the problem of statistical inference in multivariate linear regression models when the errors involved are non normally distributed. We consider multivariate t-distribution, a fat-tailed distribution, for the errors as alternative to normal distribution. Such non normality is commonly observed in working with many data sets, e.g., financial data that are usually having excess kurtosis. This distribution has a number of applications in many other areas of research as well. We use modifie...
Attitudes and achievement in statistics ameta analysis study Emmıoglu, Esma; Çapa Aydın, Yeşim (2012-11-01)
Marginalized transition random effect models for multivariate longitudinal binary data İlk Dağ, Özlem (Wiley, 2007-03-01) Generalized linear models with random effects and/or serial dependence are commonly used to analyze longitudinal data. However, the computation and interpretation of marginal covariate effects can be difficult. This led Heagerty (1999, 2002) to propose models for longitudinal binary data in which a logistic regression is first used to explain the average marginal response. The model is then completed by introducing a conditional regression that allows for the longitudinal, within-subject, dependence, either...
Estimation of response errors in complex sample surveys Fahmi, Fidan Mahmut; Öztaş, H. Ayhan; Batmaz, İnci; Department of Statistics (2013) In this thesis, simple and correlated response errors are investigated. The optimum interviewer allocation settings has been investigated by using different experimental design models (Nested design, Nested and factorial factors design and Split plot design). The proposed designs considers several stages of an interactive process. Several linear and multiplicative models have been used to explain the factors effecting nonsampling errors. This naturally includes response error models. The response error mode...
Robust estimation and hypothesis testing under short-tailedness and inliers Akkaya, Ayşen (Springer Science and Business Media LLC, 2005-06-01) Estimation and hypothesis testing based on normal samples censored in the middle are developed and shown to be remarkably efficient and robust to symmetric short-tailed distributions and to inliers in a sample. This negates the perception that sample mean and variance are the best robust estimators in such situations (Tiku, 1980; Dunnett, 1982).

Citation Formats

K. Bayramoğlu, “Estimation in interval censored data,” Ph.D. - Doctoral Program, Middle East Technical University, 2014.