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Related papers: Estimation of relative risk, odds ratio and their …

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Sequential estimators are proposed for the relative risk, odds ratio, log relative risk or log odds ratio of a dichotomous attribute in two populations. The estimators take the same number of observations from each population, and guarantee…

Methodology · Statistics 2026-04-07 Luis Mendo

Two sequential estimators are proposed for the odds p/(1-p) and log odds log(p/(1-p)) respectively, using independent Bernoulli random variables with parameter p as inputs. The estimators are unbiased, and guarantee that the variance of the…

Statistics Theory · Mathematics 2025-01-07 Luis Mendo

Some ratio estimators for estimating the population mean of the variable under study, which make use of information regarding the population proportion possessing certain attribute, are proposed. Under simple random sampling without…

General Mathematics · Mathematics 2009-07-27 Rajesh Singh , Pankaj Chauhan , Nirmala Sawan , Florentin Smarandache

In order to estimate the population mean in the presence of both non-response and measurement errors that are uncorrelated, the paper presents some novel estimators employing ranked set sampling by utilizing auxiliary information.Up to the…

Methodology · Statistics 2023-11-06 Rajesh Singh , Anamika Kumari

Sequential estimation of the success probability $p$ in inverse binomial sampling is considered in this paper. For any estimator $\hat p$, its quality is measured by the risk associated with normalized loss functions of linear-linear or…

Statistics Theory · Mathematics 2018-12-18 Luis Mendo

In this article we have suggested an improved estimator for estimating the population mean in simple random sampling using auxiliary information under the presence of measurement errors. The mean square error (MSE) of the proposed estimator…

Applications · Statistics 2013-12-05 Sachin Malik , Jayant Singh , Rajesh Singh

Many randomized approximation algorithms operate by giving a procedure for simulating a random variable $X$ which has mean $\mu$ equal to the target answer, and a relative standard deviation bounded above by a known constant $c$. Examples…

Computation · Statistics 2019-08-16 Mark Huber

In this paper we have suggested a family of estimators for the population mean when study variable itself is qualitative in nature. Expressions for the bias and mean square error (MSE) of the suggested family have been obtained. An…

General Mathematics · Mathematics 2011-03-30 Rajesh Singh , Mukesh Kumar , Florentin Smarandache

Relative error estimation has been recently used in regression analysis. A crucial issue of the existing relative error estimation procedures is that they are sensitive to outliers. To address this issue, we employ the $\gamma$-likelihood…

Methodology · Statistics 2018-10-17 Kei Hirose , Hiroki Masuda

An effective two-stage method for an estimation of parameters of the linear regression is considered. For this purpose we introduce a certain quasi-estimator that, in contrast to usual estimator, produces two alternative estimates. It is…

Statistics Theory · Mathematics 2010-10-06 Anatoly Gordinsky

The odds ratio measure is used in health and social surveys where the odds of a certain event is to be compared between two populations. It is defined using logistic regression, and requires that data from surveys are accompanied by their…

Methodology · Statistics 2014-07-01 C. Goga , A Ruiz-Gazen

Let us consider $k ~(\ge 2)$ independent populations $\Pi_1, \ldots,\Pi_k$, where $\Pi_i$ follows exponential distribution with hazard rate ${\sigma_i},$ ($i = 1,\ldots,k$). Suppose $Y_{i1},\ldots, Y_{in}$ be a random sample of size $n$…

Statistics Theory · Mathematics 2021-07-09 Brijesh Kumar Jha , Ajaya Kumar Mahapatra , Suchandan Kayal

INTRODUCTION: Wald's, the likelihood ratio (LR) and Rao's score tests and their corresponding confidence intervals (CIs), are the three most common estimators of parameters of Generalized Linear Models. On finite samples, these estimators…

Methodology · Statistics 2021-03-19 André Gillibert , Jacques Bénichou , Bruno Falissard

Suppose that $X_1,X_2,\ldots$ are a stream of independent, identically distributed Poisson random variables with mean $\mu$. This work presents a new estimate $\mu_k$ for $\mu$ with the property that the distribution of the relative error…

Computation · Statistics 2016-06-01 Mark Huber

In statistics and machine learning, logistic regression is a widely-used supervised learning technique primarily employed for binary classification tasks. When the number of observations greatly exceeds the number of predictor variables, we…

Machine Learning · Statistics 2024-04-02 Agniva Chowdhury , Pradeep Ramuhalli

Network sampling is used around the world for surveys of vulnerable, hard-to-reach populations including people at risk for HIV, opioid misuse, and emerging epidemics. The sampling methods include tracing social links to add new people to…

Methodology · Statistics 2020-02-05 Steve Thompson

The paper is focused on the problem of estimating the probability $p$ of individual contaminated sample, under group testing. The precision of the estimator is given by the probability of proportional closeness, a concept defined in the…

Statistics Theory · Mathematics 2017-12-27 Yaakov Malinovsky , Shelemyahu Zacks

A general family of estimators for estimating the population mean of the variable under study, which make use of known value of certain population parameter(s), is proposed. Under Simple Random Sampling Without Replacement (SRSWOR) scheme,…

Statistics Theory · Mathematics 2007-10-17 M. Khoshnevisan , Rajesh Singh , Pankaj Chauhan , Nirmala Sawan , Florentin Smarandache

In this paper we have proposed a median based estimator using known value of some population parameter(s) in simple random sampling. Various existing estimators are shown particular members of the proposed estimator. The bias and mean…

Statistics Theory · Mathematics 2014-08-15 Hemant K. Verma , Rajesh Singh , Florentin Smarandache

Reparameterization (RP) and likelihood ratio (LR) gradient estimators are used to estimate gradients of expectations throughout machine learning and reinforcement learning; however, they are usually explained as simple mathematical tricks,…

Machine Learning · Computer Science 2021-06-01 Paavo Parmas , Masashi Sugiyama
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