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In this paper, we study the classical problem of estimating the proportion of a finite population. First, we consider a fixed sample size method and derive an explicit sample size formula which ensures a mixed criterion of absolute and…

Statistics Theory · Mathematics 2009-02-03 Xinjia Chen

In this paper, we develop an approach for the exact determination of the minimum sample size for the estimation of a Poisson parameter with prescribed margin of error and confidence level. The exact computation is made possible by reducing…

Statistics Theory · Mathematics 2008-06-19 Xinjia Chen

In this paper, we develop an approach for the exact determination of the minimum sample size for estimating the parameter of an integer-valued random variable, which is parameterized by its expectation. Under some continuity and unimodal…

Statistics Theory · Mathematics 2012-11-20 Xinjia Chen , Zhengjia Chen

It is a common contention that it is an ``impossible mission'' to exactly determine the minimum sample size for the estimation of a binomial parameter with prescribed margin of error and confidence level. In this paper, we investigate such…

Statistics Theory · Mathematics 2007-08-02 Xinjia Chen

Computational method for statistical measures of reliability, confidence, and assurance are available for infinite population size. If the population size is finite and small compared to the number of samples tested, these computational…

Information Theory · Computer Science 2023-05-29 Sanjay M. Joshi

We first review existing sequential methods for estimating a binomial proportion. Afterward, we propose a new family of group sequential sampling schemes for estimating a binomial proportion with prescribed margin of error and confidence…

Statistics Theory · Mathematics 2013-11-05 Zhengjia Chen , Xinjia Chen

We investigate Bayesian predictive inference for finite population quantities when there are unequal probabilities of selection. Only limited information about the sample design is available; i.e., only the first-order selection…

Methodology · Statistics 2018-04-10 Junheng Ma , Joe Sedransk , Balgobin Nandram , Lu Chen

Empirical best prediction (EBP) is a well-known method for producing reliable proportion estimates when the primary data source provides only small or no sample from finite populations. There are potential challenges in implementing…

Methodology · Statistics 2025-01-22 Aditi Sen , Partha Lahiri

The problem of estimation of the proportion of units with a given attribute in a~finite population is considered. From the population a sample is drawn due to the simple random sampling without replacement. There are limited funds for…

Statistics Theory · Mathematics 2019-03-26 Dominik Sieradzki , Wojciech Zieliński

While conformal predictors reap the benefits of rigorous statistical guarantees on their error frequency, the size of their corresponding prediction sets is critical to their practical utility. Unfortunately, there is currently a lack of…

Machine Learning · Statistics 2024-03-12 Guneet S. Dhillon , George Deligiannidis , Tom Rainforth

The goal of any estimation study is an interval estimation of a the parameter(s) of interest. These estimations are mostly expressed using empirical confidence intervals that are based on sample point estimates of the corresponding…

Methodology · Statistics 2018-07-03 Ilya Novikov

Capture-recapture methods aim to estimate the size of a closed population on the basis of multiple incomplete enumerations of individuals. In many applications, the individual probability of being recorded is heterogeneous in the…

Methodology · Statistics 2016-06-08 James E. Johndrow , Kristian Lum , Daniel Manrique-Vallier

The problem of estimating a proportion of objects with particular attribute in a finite population is considered. This paper shows an example of the application of estimation fraction using new proposed sample allocation in a population…

Applications · Statistics 2019-03-19 Dominik Sieradzki , Wojciech Zieliński

The Central Limit Theorem provides a foundation for inferential statistics and hypothesis testing. It describes how standardized statistics behave under repeated sampling from large populations. However, if the size of the sample (n)…

Methodology · Statistics 2026-05-19 Mike Crowhurst

Epidemiologic screening programs often make use of tests with small, but non-zero probabilities of misdiagnosis. In this article, we assume the target population is finite with a fixed number of true cases, and that we apply an imperfect…

Methodology · Statistics 2024-04-22 Lin Ge , Yuzi Zhang , Lance A. Waller , Robert H. Lyles

The probabilities of causation are commonly used to solve decision-making problems. Tian and Pearl derived sharp bounds for the probability of necessity and sufficiency (PNS), the probability of sufficiency (PS), and the probability of…

Artificial Intelligence · Computer Science 2022-10-12 Ang Li , Ruirui Mao , Judea Pearl

A simple analytical framework to study the molecular quasispecies evolution of finite populations is proposed, in which the population is assumed to be a random combination of the constiyuent molecules in each generation,i.e., linkage…

Statistical Mechanics · Physics 2016-08-31 Domingos Alves , J. F. Fontanari

Estimating the mode of a unimodal distribution is a classical problem in statistics. Although there are several approaches for point-estimation of mode in the literature, very little has been explored about the interval-estimation of mode.…

Statistics Theory · Mathematics 2025-04-01 Manit Paul , Arun Kumar Kuchibhotla

We consider interval estimation of the difference between two binomial proportions. Several methods of constructing such an interval are known. Unfortunately those confidence intervals have poor coverage probability: it is significantly…

Methodology · Statistics 2019-03-11 Wojciech Zieliński

Estimates of population size for hidden and hard-to-reach individuals are of particular interest to health officials when health problems are concentrated in such populations. Efforts to derive these estimates are often frustrated by a…

Social and Information Networks · Computer Science 2017-02-01 Bilal Khan , Hsuan-Wei Lee , Kirk Dombrowski
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