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TITLE
DECLARATION
CERTIFICATE
ACKNOWLEDGEMENT
ABSTRACT
CONTENTS
1. INTRODUCTION
1.1 Statistical methods in reliability
1.2 Reliability analysis in discrete time
1.3 Geometric distribution - A useful model in discrete time
1.4 Bayesian estimation
1.5 Outline of the present study
2. ON THE DETERMINATION OF THE NUMBER OF OUTLIERS IN A GEOMETRIC SAMPLE
2.1 Introduction
2.2 Detection of the number of outliers by the least square method based on the survival function
2.3 Detection of the number of outliers based on posterior density
2.4 Detection of the number of outliers by the least square method based on the empirical distribution function
2.5 Simulation study and discussion
3. ESTIMATION OF THE RELIABILITY MEASURES OF GEOMETRIC DISTRIBUTION IN THE PRESENCE OF OUTLIERS
3.1 Introduction
3.2 The model
3.3 Estimation of the reliability measures under the identified model
3.4 Estimation of the reliability measures under the exchangeable model
3.5 Estimation of the reliability measures under a right censored model
3.6 Simulation study and discussion
4. ESTIMATION OF THE RELIABILITY MEASURES OF GEOMETRIC DISTRIBUTION USING RECORDS
4.1 Introduction
4.2 Estimation of the survival function
4.3 Estimation of the hazard function
4.4 Estimation of the mean residual life function
4.5 Estimation of the reliability measures using complete data
4.6 Simulation study and discussion
5. ESTIMATION OF THE RESIDUAL ENTROPY FUNCTION OF GEOMETRIC DISTRIBUTION
5.1 Introduction
5.2 Estimation of the residual entropy function when outliers arepresent in the sample
5.3 Estimation of the residual entropy function using record values
5.4 Simulation study and discussion
6. SEMIPARAMETRIC ESTIMATION ON GEOMETRIC DISTRIBUTION
6.1 Introduction
6.2 Estimation of the geometric parameter and the reliability measures using complete data
6.3 Estimation of the geometric parameter and reliability measures using Type I censored data
6.4 Simulation study and discussion
6.5 Plan for future study
REFERENCES
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