الفهرس | Only 14 pages are availabe for public view |
Abstract The statistics of record-breaking events have been of great interest not only to statisticians and scientists, but also from the general public. In some experiments and studies one can observe or record only the observations that are more extreme than the current extreme value. This type of data is called records values and has been applied in many fields. The first contribution in this thesis is deriving some statistical properties of the generalized inverted exponential distribution based on upper record values and upper record ranked set sampling schemes. Bayesian estimation technique is used to estimate the population parameters of the generalized inverted exponential distribution based on the two sampling techniques. The Markov Chain Monte Carlo method is developed due to the lack of explicit forms for the Bayesian estimates. A Simulation study is implemented to compute and compare the performance of estimates in both sampling schemes with respect to relative absolute biases, estimated risks and the width of credible intervals |