Fast algorithms of computing admissible intervals for discrete distributions with single parameter

It is of great interest to compute optimal exact confidence intervals for the success probability (p) in a binomial distribution, the number of subjects with a certain attribute (M) or the total number of subjects (N) in a hypergeometric distribution, and the mean λ of a Poisson distribution. In thi...

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Published in:Journal of applied statistics Vol. 52; no. 3; pp. 687 - 701
Main Authors: Wang, Weizhen, Yu, Chongxiu, Zhang, Zhongzhan
Format: Journal Article
Language:English
Published: England Taylor & Francis 2025
Taylor & Francis Ltd
Subjects:
62-08
Algorithms
Bisection method
Clopper-Pearson-type interval
Confidence intervals
exact confidence interval
infimum coverage probability
monotonic confidence limits
Parameters
Poisson distribution
Statistical analysis
monotonic confidence limits
Clopper-Pearson-type interval
infimum coverage probability
62-08
Bisection method
62F99
exact confidence interval
ISSN:0266-4763, 1360-0532
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Abstract It is of great interest to compute optimal exact confidence intervals for the success probability (p) in a binomial distribution, the number of subjects with a certain attribute (M) or the total number of subjects (N) in a hypergeometric distribution, and the mean λ of a Poisson distribution. In this paper, efficient algorithms are proposed to compute an admissible exact interval for each of the four parameters when the sample size (n) or the random observation X is large. The algorithms are utilized in four practical examples: evaluating the relationship between two diseases, certifying companies, estimating the proportion of drug users, and analyzing earthquake frequency. The intervals computed by the algorithms are shorter, and the calculations are faster, demonstrating the accuracy of the results and the time efficiency of the proposed algorithms.
AbstractList It is of great interest to compute optimal exact confidence intervals for the success probability (p) in a binomial distribution, the number of subjects with a certain attribute (M) or the total number of subjects (N) in a hypergeometric distribution, and the mean λ of a Poisson distribution. In this paper, efficient algorithms are proposed to compute an admissible exact interval for each of the four parameters when the sample size (n) or the random observation X is large. The algorithms are utilized in four practical examples: evaluating the relationship between two diseases, certifying companies, estimating the proportion of drug users, and analyzing earthquake frequency. The intervals computed by the algorithms are shorter, and the calculations are faster, demonstrating the accuracy of the results and the time efficiency of the proposed algorithms.It is of great interest to compute optimal exact confidence intervals for the success probability (p) in a binomial distribution, the number of subjects with a certain attribute (M) or the total number of subjects (N) in a hypergeometric distribution, and the mean λ of a Poisson distribution. In this paper, efficient algorithms are proposed to compute an admissible exact interval for each of the four parameters when the sample size (n) or the random observation X is large. The algorithms are utilized in four practical examples: evaluating the relationship between two diseases, certifying companies, estimating the proportion of drug users, and analyzing earthquake frequency. The intervals computed by the algorithms are shorter, and the calculations are faster, demonstrating the accuracy of the results and the time efficiency of the proposed algorithms.
It is of great interest to compute optimal exact confidence intervals for the success probability (p) in a binomial distribution, the number of subjects with a certain attribute (M) or the total number of subjects (N) in a hypergeometric distribution, and the mean λ of a Poisson distribution. In this paper, efficient algorithms are proposed to compute an admissible exact interval for each of the four parameters when the sample size (n) or the random observation X is large. The algorithms are utilized in four practical examples: evaluating the relationship between two diseases, certifying companies, estimating the proportion of drug users, and analyzing earthquake frequency. The intervals computed by the algorithms are shorter, and the calculations are faster, demonstrating the accuracy of the results and the time efficiency of the proposed algorithms.
It is of great interest to compute optimal exact confidence intervals for the success probability ( ) in a binomial distribution, the number of subjects with a certain attribute ( ) or the total number of subjects ( ) in a hypergeometric distribution, and the mean of a Poisson distribution. In this paper, efficient algorithms are proposed to compute an admissible exact interval for each of the four parameters when the sample size ( ) or the random observation is large. The algorithms are utilized in four practical examples: evaluating the relationship between two diseases, certifying companies, estimating the proportion of drug users, and analyzing earthquake frequency. The intervals computed by the algorithms are shorter, and the calculations are faster, demonstrating the accuracy of the results and the time efficiency of the proposed algorithms.
Author Yu, Chongxiu
Wang, Weizhen
Zhang, Zhongzhan
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Cites_doi 10.2307/2333958
10.12776/qip.v23i2.1277
10.1161/JAHA.120.016997
10.1016/0167-7152(94)00166-6
10.1080/01621459.2014.966191
10.2105/AJPH.2018.304873
10.1093/biomet/26.4.404
10.1137/1110022
10.2307/3315916
10.1214/ss/1009213286
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Issue 3
Keywords monotonic confidence limits
Clopper-Pearson-type interval
infimum coverage probability
62-08
Bisection method
62F99
exact confidence interval
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References e_1_3_2_9_1
e_1_3_2_18_1
e_1_3_2_7_1
Bol'shev L.N. (e_1_3_2_5_1) 1965; 10
Wang W. (e_1_3_2_19_1) 2014; 24
e_1_3_2_10_1
e_1_3_2_11_1
e_1_3_2_6_1
Konijn H.S. (e_1_3_2_13_1) 1973
e_1_3_2_4_1
e_1_3_2_3_1
Wang H. (e_1_3_2_17_1) 2007; 17
Razavi A.C. (e_1_3_2_15_1) 2020; 9
Thompson S.K. (e_1_3_2_16_1) 2002
Chapman D.G. (e_1_3_2_8_1) 1951; 1
Khurshid A. (e_1_3_2_12_1) 2010; 6
Agresti A. (e_1_3_2_2_1) 2013
Lehmann E.L. (e_1_3_2_14_1) 2005
References_xml – volume-title: Categorical Data Analysis
  year: 2013
  ident: e_1_3_2_2_1
– volume-title: Sampling
  year: 2002
  ident: e_1_3_2_16_1
– ident: e_1_3_2_10_1
  doi: 10.2307/2333958
– ident: e_1_3_2_6_1
  doi: 10.12776/qip.v23i2.1277
– volume: 9
  start-page: e016997
  year: 2020
  ident: e_1_3_2_15_1
  article-title: Cardiovascular disease prevention and implications of coronavirus disease 2019: An evolving case study in the Crescent City
  publication-title: J. Am. Heart Assoc.
  doi: 10.1161/JAHA.120.016997
– volume: 6
  start-page: 75
  year: 2010
  ident: e_1_3_2_12_1
  article-title: Binomial and Poisson confidence intervals and its variants: A bibliography
  publication-title: Pak. J. Sci. Res.
– volume-title: Statistical Theory of Sample Survey Design and Analysis
  year: 1973
  ident: e_1_3_2_13_1
– volume: 1
  start-page: 131
  year: 1951
  ident: e_1_3_2_8_1
  article-title: Some properties of the hypergeometric distribution with application to zoological sample censuses
  publication-title: Calif. Publ. Stat.
– ident: e_1_3_2_11_1
  doi: 10.1016/0167-7152(94)00166-6
– ident: e_1_3_2_18_1
  doi: 10.1080/01621459.2014.966191
– ident: e_1_3_2_3_1
  doi: 10.2105/AJPH.2018.304873
– volume-title: Testing Statistical Hypotheses
  year: 2005
  ident: e_1_3_2_14_1
– ident: e_1_3_2_9_1
  doi: 10.1093/biomet/26.4.404
– volume: 17
  start-page: 361
  year: 2007
  ident: e_1_3_2_17_1
  article-title: Exact confidence coefficients of confidence intervals for a binomial proportion
  publication-title: Stat. Sin.
– volume: 10
  start-page: 173
  year: 1965
  ident: e_1_3_2_5_1
  article-title: On the construction of confidence limits
  publication-title: Theor. Probab. Appl+.
  doi: 10.1137/1110022
– ident: e_1_3_2_4_1
  doi: 10.2307/3315916
– volume: 24
  start-page: 1389
  year: 2014
  ident: e_1_3_2_19_1
  article-title: An iterative construction of confidence intervals for a proportion
  publication-title: Stat. Sin.
– ident: e_1_3_2_7_1
  doi: 10.1214/ss/1009213286
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Snippet It is of great interest to compute optimal exact confidence intervals for the success probability (p) in a binomial distribution, the number of subjects with a...
It is of great interest to compute optimal exact confidence intervals for the success probability ( ) in a binomial distribution, the number of subjects with a...
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SubjectTerms 62-08
Algorithms
Bisection method
Clopper-Pearson-type interval
Confidence intervals
exact confidence interval
infimum coverage probability
monotonic confidence limits
Parameters
Poisson distribution
Statistical analysis
Title Fast algorithms of computing admissible intervals for discrete distributions with single parameter
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