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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 propose two-stage and sequential procedures to estimate the unknown parameter N of a binomial distribution with unknown parameter p, when we reinforce data with an independent sample of a negative-binomial experiment having the same p.

Methodology · Statistics 2022-04-14 Yaakov Malinovsky , Shelemyahu Zacks

In this paper, we develop a multistage approach for estimating the mean of a bounded variable. We first focus on the multistage estimation of a binomial parameter and then generalize the estimation methods to the case of general bounded…

Statistics Theory · Mathematics 2009-04-27 Xinjia Chen

The negative binomial distribution has been widely used as a more flexible model than the Poisson distribution for count data. However, when the true data-generating process is Poisson, it is often challenging to distinguish it from a…

Statistics Theory · Mathematics 2026-04-07 Yingying Yang , Niloufar Dousti Mousavi , Zhou Yu , Jie Yang

In this paper, we have established a unified framework of multistage parameter estimation. We demonstrate that a wide variety of statistical problems such as fixed-sample-size interval estimation, point estimation with error control,…

Statistics Theory · Mathematics 2013-11-05 Xinjia Chen

In this paper we develop a very general class of bivariate discrete distributions. The basic idea is very simple. The marginals are obtained by taking the random geometric sum of a baseline distribution function. The proposed class of…

Methodology · Statistics 2018-05-22 Debasis Kundu

Compound Poisson distributions have been employed by many authors to fit experimental data, typically via the method of moments or maximum likelihood estimation. We propose a new technique and apply it to several sets of published data. It…

Methodology · Statistics 2025-04-01 S. R. Mane

A results of numerical procedure for construction of confidence intervals for parameter of Poisson distribution for signal in the presence of background which has Poisson distribution with known value of parameter are presented. It is shown…

Data Analysis, Statistics and Probability · Physics 2007-05-23 S. I. Bityukov , N. V. Krasnikov

In this paper, we have established a new framework of truncated inverse sampling for estimating mean values of non-negative random variables such as binomial, Poisson, hyper-geometrical, and bounded variables. We have derived explicit…

Statistics Theory · Mathematics 2013-11-05 Xinjia Chen

A Poisson Binomial distribution over $n$ variables is the distribution of the sum of $n$ independent Bernoullis. We provide a sample near-optimal algorithm for testing whether a distribution $P$ supported on $\{0,...,n\}$ to which we have…

Data Structures and Algorithms · Computer Science 2014-10-15 Jayadev Acharya , Constantinos Daskalakis

Results of numerical procedure of constructing confidence intervals for parameter of the Poisson distribution of signal events in the presence of background events with known value of parameter of Poisson distribution are presented. It is…

High Energy Physics - Experiment · Physics 2007-05-23 S. I. Bityukov , N. V. Krasnikov , V. A. Taperechkina

In this paper, we consider Bayesian point estimation and predictive density estimation in the binomial case. After presenting preliminary results on these problems, we compare the risk functions of the Bayes estimators based on the…

Statistics Theory · Mathematics 2021-09-13 Yasuyuki Hamura

The exact expression is derived for the expected value, $< {p_i}> $, for the parameter for any bin $i$ of a histogram following a multinomial distribution derived by sorting $N$ observations into bins of $B$ classes, if $n_i$ of the…

Statistics Theory · Mathematics 2013-03-18 Jonathan M. Friedman

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

Although the specification of bivariate probability models using a collection of assumed conditional distributions is not a novel concept, it has received considerable attention in the last decade. In this study, a bivariate…

Methodology · Statistics 2025-03-20 Indranil Ghosh , Mina Norouzirad , Filipe J. Marques

This paper proposes a Bayesian method for estimating the parameters of a normal distribution when only limited summary statistics (sample mean, minimum, maximum, and sample size) are available. To estimate the parameters of a normal…

Methodology · Statistics 2024-11-21 Tomoki Matsumoto

We present two different approaches for parameter learning in several mixture models in one dimension. Our first approach uses complex-analytic methods and applies to Gaussian mixtures with shared variance, binomial mixtures with shared…

Machine Learning · Computer Science 2020-01-22 Akshay Krishnamurthy , Arya Mazumdar , Andrew McGregor , Soumyabrata Pal

In this paper, we begin our discussion with some of the well-known methods available in the literature for the estimation of the parameters of a univariate/multivariate stable distribution. Based on the available methods, a new hybrid…

Computation · Statistics 2019-02-27 Aastha M. Sathe , Neelesh. S. Upadhye

In this paper, we have developed new multistage tests which guarantee prescribed level of power and are more efficient than previous tests in terms of average sampling number and the number of sampling operations. Without truncation, the…

Statistics Theory · Mathematics 2011-06-14 Xinjia Chen

The empirical probability density function for the conditional distribution of the true value of Poisson distribution parameter on one measurement is constructed by computer experiment. The analysis of the obtained distributions confirms…

Data Analysis, Statistics and Probability · Physics 2009-11-10 S. I. Bityukov , V. A. Medvedev , V. V. Smirnova , Yu. V. Zernii
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