兩階段取樣法下指數分布的概似推論

機構典藏 > College of Sciences > Department of Applied Mathematics and Data Science > Thesis > Item 987654321/32890

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/32890

Title:	兩階段取樣法下指數分布的概似推論
Other Titles:	Exact likelihood inference for the exponential distribution base on two-stage sampling
Authors:	張家賓;Chang, Jia-bin
Contributors:	淡江大學數學學系碩士班伍志祥;Wu, Jyh-shyang
Keywords:	兩階段取樣法;指數分布;概似推論;two–stage sampling;likelihood inference;Exponential distribution
Date:	2008
Issue Date:	2010-01-11 02:56:21 (UTC+8)
Abstract:	型I、型II及混合型設限資料所產生的問題，一是觀測樣本個數太少，使得統計分析效率不高，二是觀測時間過長，導致成本提高。為了解決這兩難的情形，本論文中，在有一最長觀測時間的設限下，我們提出了兩階段取樣法，並設定一參考時間及一勉強可接受的樣本數，來作為是否進行第二階段觀測的準則。這樣不僅能得到可接受的樣本數，更能縮短觀測時間，節省長時間觀測下所花費的大量成本。當隨機樣本的壽命服從參數theta的指數分配時，我們討論theta的最大概似估計量，及其機率分配、信賴區間…等問題，並用一實例來探討此取樣法。 In a life testing experiment, Type-I, Type-II, and Hybrid censored samples generally lead into some disadvantages, one is that it is inefficient to analyze because of the few number of failures, the other is that the cost becomes higher for a long observing time. In this paper, under the end time of sampling period censored, we propose two-stage sampling and set a criteria to determine whether to proceed to the second stage or not. Using this method, we can not only get an acceptable number of failures but also decrease the observing time to save the cost of the experiment. When the n units are put on test and the failure times are independent and identically distributed as exponential with parameter theta, we discuss the maximum likelihood estimator, the probability density function, the confidence interval of theta . We also present one sample to illustrate all the results finally.
Appears in Collections:	[Department of Applied Mathematics and Data Science] Thesis

Files in This Item:

File	Size	Format
	0Kb	Unknown	306	View/Open

Loading...