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Estimation Parameters in Geometric Distribution from Censored Data

Author: JiangMei
Tutor: DingBangJun
School: East China Normal University
Course: Probability Theory and Mathematical Statistics
Keywords: Group data Interval censored data Geometric distribution MLE Iterated Method MC Iterated Method
CLC: O212.1
Type: Master's thesis
Year: 2009
Downloads: 122
Quote: 1
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Abstract


In many research areas, such as industry, agriculture, medicine, economics, actuarial science and biological sciences, the data we have carried out statistical inference and hypothesis testing to analyze often can not be accurately observed. These observational data or a known specific observation falls within the range, or known or more than a single observation point in time, we call such a data type censored data. In recent years, censored data research statistician who has been gradually importance, especially for the interval censored data of the study, the emergence of a broad field in various disciplines. In the interval censored data of the study, study of parameter estimation to occupy a very important part of statisticians made a rich and effective methods of estimation, and a wide range of in-depth study.In this paper, under the exponential distribution in the comparison of two methods of estimation of the advantages and disadvantages of iteration, while these two approaches to the geometric parameters. There are four sections of this article. The first chapter introduces the definition of censored data, as well as its breadth, and introduced a number of censored data approach; chapter II iterative methods for stochastic simulation to compare their strengths and weaknesses; Chapter III of the two iterative methods to promote, and put it under the geometric distribution used to estimate parameters, and proves the convergence of iterative methods from the theoretical; Chapter IV of the issue can be discussed further.

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CLC: > Mathematical sciences and chemical > Mathematics > Probability Theory and Mathematical Statistics > Mathematical Statistics > General mathematical statistics
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