以貝氏方法處理部分區分（partially-classified）失去部分訊息資料的類別抽樣（categorical sampling with censored data）的研究已行之有年，但大部分都在“失去部分訊息但無價值性”（non-informative censoring）以及“誠實回答”（truthful reporting）的前提下。Thomas J. Jiang取消以上二個限制，於1995年提quasi-Bayes method來近似這類問題的貝氏解。而Paulino and Pereira亦於1995年提出另一方法求得貝氏解。本文重點在於比較此二種方法，亦探討Thomas J. Jiang之quasi-Bayes method之收斂性。

Bayesian treatments of categorical sampling with censored （partially-classified）data have been subjected to research for decades, but most of these researches focused on the analysis of categorical date under non-informative censoring and truthful reporting Thomas J. Jiang dropped these assumptions and proposed quasi-Bayes method to approximate a coherent Bayes solution in 1995. Paulino and Pereira also proposed another method to get Bayes solution In the paper, we shall compare these two methods and study the convergence of quasi-Bayes method..........

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