4.2 Article

Logarithmic confidence intervals for the cross-product ratio of binomial proportions under different sampling schemes

期刊

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/03610918.2021.1914090

关键词

Cross-product ratio; Direct binomial sampling scheme; Inverse binomial sampling scheme; Logarithmic confidence interval; Normal approximation

向作者/读者索取更多资源

We investigated the problem of logarithmic interval estimation for a cross-product ratio with data from two independent Bernoulli samples. Asymptotic logarithmic confidence intervals were constructed under different types of sampling schemes, and the parameter estimators showed exponentially decreasing bias. Our findings suggest that the relatively simple normal approximations are reliable for constructing logarithmic confidence intervals.
We consider the problem of logarithmic interval estimation for a cross-product ratio rho=p(1)(1-p(2))/p(2)(1-p(1)) with data from two independent Bernoulli samples. Each sample may be obtained in the framework of direct or inverse Binomial sampling schemes. Asymptotic logarithmic confidence intervals are constructed under different types of sampling schemes, with parameter estimators demonstrating exponentially decreasing bias. Our goal is to investigate the cases when the relatively simple normal approximations for estimators of the cross-product ratio are reliable for constructing logarithmic confidence intervals. We use the closeness of the confidence coefficient to the nominal confidence level as our main evaluation criterion, and use the Monte-Carlo method to investigate the key probability characteristics of intervals corresponding to all possible combinations of sampling schemes. We present estimations of the coverage probability, expectation and standard deviation of interval widths in tables. Also, we provide some recommendations for applying each logarithmic interval obtained.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.2
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据