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Related papers: A solution in small area estimation problems

200 papers

The paper delineates a proper statistical setting for defining the sampling design for a small area estimation problem. This problem is often treated only via indirect estimation using the values of the variable of interest also from…

Methodology · Statistics 2023-03-16 Piero Demetrio Falorsi , Stefano Falorsi , Vincenzo Nardelli , Paolo Righi

Sample surveys are widely used to obtain information about totals, means, medians, and other parameters of finite populations. In many applications, similar information is desired for subpopulations such as individuals in specific…

Methodology · Statistics 2017-05-30 Jiahua Chen , Yukun Liu

Using sample surveys as a cost effective tool to provide estimates for characteristics of interest at population and sub-populations (area/domain) level has a long tradition in "small area estimation". However, the existence of outliers in…

Methodology · Statistics 2021-01-13 Setareh Ranjbar , Elvezio Ronchetti , Stefan Sperlich

Auxiliary information is increasingly available from administrative and other data sources, but it is often incomplete and of non-probability origin. We propose a two-step small area estimation approach in which the first step relies on…

Methodology · Statistics 2026-02-16 Donatas Šlevinskas , Ieva Burakauskaitė , Andrius Čiginas

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 present paper discusses the problem of estimating the finite population mean of study variable in simple random sampling in the presence of non response and response error together. The estimators in this article use auxiliary…

Methodology · Statistics 2014-04-08 Prayas Sharma , Rajesh Singh

When doing impact evaluation and making causal inferences, it is important to acknowledge the heterogeneity of the treatment effects for different domains (geographic, socio-demographic, or socio-economic). If the domain of interest is…

Methodology · Statistics 2021-03-12 Setareh Ranjbar , Nicola Salvati , Barbara Pacini

The purpose of writing this book is to suggest some improved estimators using auxiliary information in sampling schemes like simple random sampling and systematic sampling. This volume is a collection of five papers. The following problems…

Statistics Theory · Mathematics 2013-08-28 Rajesh Singh , Florentin Smarandache

Area-specific causal inference is important in many policy and survey applications, where the goal is to evaluate treatment effects for small geographic or demographic domains. Existing causal small area estimation methods, however,…

Statistics Theory · Mathematics 2026-05-06 Tsubasa Ito , Shonosuke Sugasawa

We consider stochastic optimization problems which use observed data to estimate essential characteristics of the random quantities involved. Sample average approximation (SAA) or empirical (plug-in) estimation are very popular ways to use…

Statistics Theory · Mathematics 2021-03-16 Darinka Dentcheva , Yang Lin

In countries where population census data are limited, generating accurate subnational estimates of health and demographic indicators is challenging. Existing model-based geostatistical methods leverage covariate information and spatial…

Methodology · Statistics 2022-08-08 Peter A. Gao , Jon Wakefield

Small area estimation has become an important tool in official statistics, used to construct estimates of population quantities for domains with small sample sizes. Typical area-level models function as a type of heteroscedastic regression,…

Methodology · Statistics 2022-09-07 Paul A. Parker , Scott H. Holan , Ryan Janicki

The present study discuss the problem of estimating the finite population mean using auxiliary attribute in stratified random sampling. In this paper taking the advantage of point bi-serial correlation between the study variable and…

Statistics Theory · Mathematics 2014-08-13 Hemant K. Verma , Prayas Sharma , Rajesh Singh

The statistical challenges in using big data for making valid statistical inference in the finite population have been well documented in literature. These challenges are due primarily to statistical bias arising from under-coverage in the…

Methodology · Statistics 2020-06-19 Jae-kwang Kim , Siu-Ming Tam

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation…

Applications · Statistics 2016-11-14 Dennis M. Feehan , Matthew J. Salganik

Nested error regression models are useful tools for analysis of grouped data, especially in the case of small area estimation. This paper suggests a nested error regression model using uncertain random effects in which the random effect in…

Methodology · Statistics 2017-02-28 Shonosuke Sugasawa , Tatsuya Kubokawa

This article presents the problem of estimating the population mean using auxiliary information in the presence of measurement errors. A numerical study is made among the proposed estimator, the exponential ratio estimator, Singh and…

Applications · Statistics 2014-05-19 Sachin Malik , Rajesh Singh

Model-based small area estimation is frequently used in conjunction with survey data in order to establish estimates for under-sampled or unsampled geographies. These models can be specified at either the area-level, or the unit-level, but…

Methodology · Statistics 2020-01-14 Paul A. Parker , Ryan Janicki , Scott H. Holan

A model-assisted semiparametric method of estimating finite population totals is investigated to improve the precision of survey estimators by incorporating multivariate auxiliary information. The proposed superpopulation model is a…

Methodology · Statistics 2019-03-19 Lily Wang

Analysis of sample survey data often requires adjustments to account for missing data in the outcome variables of principal interest. Standard adjustment methods based on item imputation or on propensity weighting factors rely heavily on…

Methodology · Statistics 2016-03-08 Wei-Yin Loh , John Eltinge , MoonJung Cho , Yuanzhi Li
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