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Abstract
The Rayleigh distribution is one of the oldest important distribution both on theoretical and practical grounds, especially, in the engineering, the physical and the electrical studies.
Statistical estimation is to obtain some estimates (either point or interval) for the unknown population parameters based on some given data from the same population.
On The other hand, Statistical prediction is to obtain some estimates (either point or interval) for future ”unobserved” data, rather than the population parameters, based on past (informative) data from the same population.
These available data could be obtained in many different types.
One general and important type of such data is the so called progressively type-II right censored data which will be explained in Chapter 1. The main purpose of this thesis is to obtain statistical estimation and prediction for the Rayleigh model based on progressively type-ll right censored data.
The thesis consists of three chapters.
Chapter 1, contains a historical survey on some studies in theoretical and application which have been made on Rayleigh distribution since its formation until the latest issued researches. Also, it contains some basic concepts which will be used through out this thesis.
Finally, it contains a description of the under-study problem.
Chapter 2, is devoted to find maximum likelihood (ML) and Bayes estimation for the two parameters 0 and u of the Rayleigh distribution based on progressively type-II censored samples.