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Related papers: On Estimation of Finite Population Proportion

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In this paper, we develop an exact method for the determination of the minimum sample size for estimating the proportion of a finite population with prescribed margin of error and confidence level. By characterizing the behavior of the…

Statistics Theory · Mathematics 2007-08-03 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

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

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

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

In this paper we examine the properties of the Wilson score interval, used for inferences for an unknown binomial proportion parameter. We examine monotonicity and consistency properties of the interval and we generalise it to give two…

Statistics Theory · Mathematics 2021-09-28 Ben O'Neill

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

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

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

Parameters of sub-populations can be more relevant than super-population ones. For example, a healthcare provider may be interested in the effect of a treatment plan for a specific subset of their patients; policymakers may be concerned…

Methodology · Statistics 2023-03-22 Ying Jin , Dominik Rothenhäusler

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

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

This article attempts to offer some perspectives on Bayesian inference for finite population quantities when the units in the population are assumed to exhibit complex dependencies. Beginning with an overview of Bayesian hierarchical…

Methodology · Statistics 2025-09-15 Sudipto Banerjee

Ranking populations such as institutions based on certain characteristics is often of interest, and these ranks are typically estimated using samples drawn from the populations. Due to sample randomness, it is important to quantify the…

Methodology · Statistics 2025-12-08 Onrina Chandra , Min-ge Xie

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 aim of this paper is to provide a resampling technique that allows us to make inference on superpopulation parameters in finite population setting. Under complex sampling designs, it is often difficult to obtain explicit results about…

Methodology · Statistics 2018-09-24 Pier Luigi Conti , Alberto Di Iorio

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

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

Finite population inference is a central goal in survey sampling. Probability sampling is the main statistical approach to finite population inference. Challenges arise due to high cost and increasing non-response rates. Data integration…

Methodology · Statistics 2020-01-13 Shu Yang , Jae Kwang Kim

We present a robust Bayesian method to analyze forestry data when samples are selected with probability proportional to length from a finite population of unknown size. Specifically, we use Bayesian predictive inference to estimate the…

Applications · Statistics 2019-02-13 Zhiqing Xu , Balgobin Nandram , Binod Manandhar
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