Results 31 to 40 of about 1,760,812 (299)
Simple House Needs in Jember with Robust Small Area Estimation
Jurnal Ilmu Dasar, 2017 SAE (Small Area Estimation) is often used by researchers, especially statisticians to estimate parameters of a subpopulation which has a small sample size.
Frida Murtinasari +2 more
doaj +1 more source
Multivariate small area estimation under nonignorable nonresponse
Statistical Theory and Related Fields, 2019 We consider multivariate small area estimation under nonignorable, not missing at random (NMAR) nonresponse. We assume a response model that accounts for the different patterns of the observed outcomes, (which values are observed and which ones are ...
Danny Pfeffermann, Michael Sverchkov
doaj +1 more source
An Asymmetric Area Model-Based Approach for Small Area Estimation Applied to Survey Data
Revstat Statistical Journal, 2021 The Birnbaum–Saunders distribution is asymmetrical and has received considerable attention due to its properties and its relationship with the normal distribution. In this paper, we propose a methodology for estimating the mean of small areas based on a
Marcelo Rodríguez +5 more
doaj +1 more source
Fully Bayesian Benchmarking of Small Area Estimation Models
Journal of Official Statistics, 2020 Estimates for small areas defined by social, demographic, and geographic variables are increasingly important for official statistics. To overcome problems of small sample sizes, statisticians usually derive model-based estimates.
Junni L. Zhang, John R. Bryant
semanticscholar +1 more source
Weighting and imputation comparison in small area estimation
Lietuvos Matematikos Rinkinys, 2010 In this paper, different methods of nonresponse adjustment for the totals of small area domains are examined. To improve quality of estimations linear model with random parameters at domain level is used.
Vilma Nekrašaitė-Liegė
doaj +1 more source
Precise and unbiased biomass estimation from GEDI data and the US Forest Inventory
Frontiers in Forests and Global Change, 2023 Atmospheric CO2 concentrations are dependent on land-atmosphere carbon fluxes resultant from forest dynamics and land-use changes. These fluxes are not well-constrained, in part because reliable baseline estimates of forest carbon stocks and the ...
Jamis Bruening +3 more
doaj +1 more source
Smoothing and Benchmarking for Small Area Estimation [PDF]
International Statistical Review, 2020 SummarySmall area estimation is concerned with methodology for estimating population parameters associated with a geographic area defined by a cross‐classification that may also include non‐geographic dimensions. In this paper, we develop constrained estimation methods for small area problems: those requiring smoothness with respect to similarity ...
Rebecca C. Steorts +2 more
openaire +2 more sources
Small area estimation in the case of nonesponse
Lietuvos Matematikos Rinkinys, 2009 In this paper the effect of model and nonresponseadjustment on different types of estimators for the totals of small area domains is examined. The empirical results are based on Monte Carlo simulations with repeated samples drawn from a finite population
Vilma Nekrašaitė-Liegė
doaj +1 more source
An Empirical Evaluation of Small Area Estimators [PDF]
SSRN Electronic Journal, 2003 Summary: This paper compares five small area estimators. We use Monte Carlo simulation in the context of both artificial and real populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated weights: one that assumes homogeneity of within
Àlex Costa, Albert Satorra, Eva Ventura
openaire +5 more sources
Multivariate Small Area Estimation of Multidimensional Latent Economic Well‐being Indicators
International Statistical Review, 2020 Factor analysis models are used in data dimensionality reduction problems where the variability among observed variables can be described through a smaller number of unobserved latent variables.
A. Moretti, N. Shlomo, J. Sakshaug
semanticscholar +1 more source