Journal ArticleDOI
On Some Aspects of Unbiased Estimation of Parameters in Quasi-Binomial Distributions
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TLDR
In this article, an attempt has been made to settle the question of existence of an unbiased estimator of the key parameter p of the quasi-binomial distributions of Type I (QBD I) and of Type II(QBD II), with/without any knowledge of the other parameter φ appearing in the expressions for probability functions of the QBD's.Abstract:
In this article, an attempt has been made to settle the question of existence of unbiased estimator of the key parameter p of the quasi-binomial distributions of Type I (QBD I) and of Type II (QBD II), with/without any knowledge of the other parameter φ appearing in the expressions for probability functions of the QBD's. This is studied with reference to a single observation, a random sample of finite size m as also with samples drawn by suitably defined sequential sampling rules.read more
Citations
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Journal ArticleDOI
Urn models and their applications: an approach to modern discrete probability theory, by Norman L. Johnson and Samuel Kotz. Pp xiii, 402. £16·45. 1977. SBN 0 471 44630 0 (Wiley)
Journal ArticleDOI
Boundary Crossing Random Walks, Clinical Trials, and Multinomial Sequential Estimation
Enrico Bibbona,Alessandro Rubba +1 more
TL;DR: In this paper, a sufficient condition for the uniqueness of multinomial sequential unbiased estimators is provided generalizing a classical result for binomial samples and applied to infer the parameters of multidimensional or multiinomial random walks that are observed until they reach a boundary.
Journal ArticleDOI
Boundary crossing Random Walks, clinical trials and multinomial sequential estimation
Enrico Bibbona,Alessandro Rubba +1 more
TL;DR: In this article, a sufficient condition for the uniqueness of multinomial sequential unbiased estimators is provided generalizing a classical result for binomial samples, and an application to clinical trials is presented.
References
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Journal ArticleDOI
Conditional Expectation and Unbiased Sequential Estimation
TL;DR: In this paper, it was shown that whenever there is a sufficient statistic and an unbiased estimate, not a function of $u$ only, for a parameter $\theta$, the function $E(t \mid u)$, which is a function function of u only, is an unbiased estimator with a variance smaller than that of $t.
Journal ArticleDOI
Urn models and their applications: an approach to modern discrete probability theory, by Norman L. Johnson and Samuel Kotz. Pp xiii, 402. £16·45. 1977. SBN 0 471 44630 0 (Wiley)
Book ChapterDOI
Unbiased Estimates for Certain Binomial Sampling Problems with Applications
TL;DR: In this paper, a necessary and sufficient condition that p be the unique unbiased estimate for p is given. But this condition is not satisfied, and it is not known whether more than one unbiased estimate is possible.
Journal ArticleDOI
Unbiased Sequential Estimation for Binomial Populations
TL;DR: In this article, the authors consider the problem of finding a sampling plan and an unbiased estimator for the binomial distribution, in some sense, at a specified value (p_0), of a given function, i.e., when the sampling plan to be used was given in advance.