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On the choice of the number of Monte Carlo iterations and bootstrap replicates in Empirical Best Prediction

100%
Chwila A., Żądło T.
Statistics in Transition new series
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2020
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vol. 21
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issue 2
35-60
EN
Empirical Best Predictors (EBPs) are widely used for small area estimation purposes. In the case of longitudinal surveys, this class of predictors can be used to predict any given population or subpopulation characteristic for any time period, including future periods. Generally, the value of an EBP is computed by means of Monte Carlo algorithms, while its MSE is usually estimated using the parametric bootstrap method. Model-based simulation studies of the properties of the predictors require numerous repetitions of the random generation of population data. This leads to a question about the dependence between the number of iterations in all the procedures and the stability of the results. The aim of the paper is to show this dependence and to propose methods of choosing the appropriate number of iterations in practice, using a set of real economic longitudinal data available at the United States Census Bureau website.
2
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SAMPLE ALLOCATION IN ESTIMATION OF PROPORTION IN A FINITE POPULATION DIVIDED INTO TWO STRATA: AN EXAMPLE OF APPLICATION

88%
Sieradzki D., Zieliński W.
Metody Ilościowe w Badaniach Ekonomicznych
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2018
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vol. 19
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issue 1
71-77
EN
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 divided into two strata. Variance of estimator of the proportion which uses proposed sample allocation is compared to variance of the standard one. In the paper an application of sample allocation described in Sieradzki & Zieliński [2017] is presented."
3
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Small area quantile estimation based on distribution function using linear mixed models

75%
Stachurski T.
Economics and Business Review
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2021
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vol. 7
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issue 2
97-114
EN
In economic studies researchers are oeftn interested in the estimation of the distribution function or certain functions of the distribution function such as quantiles. This work focuses on the estimation quantiles as inverses of the estimates of the distribution function in the presence of auxiliary information that is correlated with the study variable. In the paper a plug-in estimator of the distribution function is proposed which is used to obtain quantiles in the population and in the small areas. Performance of the proposed method is compared with other estimators of the distribution function and quantiles using the simulation study. The obtained results show that the proposed method usually has smaller relative biases and relative RMSE comparing to other methods of obtaining quantiles based on inverting the distribution function.
4
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Rola statystyki w życiu społeczeństwa i funkcjonowaniu państwa

51%
Iwasiewicz A.
Państwo i Społeczeństwo
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2011
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issue 2
105-132
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