scholarly journals SMALL AREA ESTIMATION METHOD WITH EMPIRICAL BAYES BASED ON BETA BINOMIAL MODEL IN GENERATED DATA

2020 ◽  
Vol 14 (1) ◽  
pp. 1-9
Author(s):  
Ferra Yanuar ◽  
Rahmatika Fajriyah ◽  
Dodi Devianto
Keyword(s):  
Binary Data ◽  
Small Area ◽  
Empirical Bayes ◽  
Small Area Estimation ◽  
Estimation Method ◽  
Estimation Methods ◽  
Auxiliary Variables ◽  
Indirect Estimation ◽  
Area Estimation ◽  
Direct Estimation

Small Area Estimation is one of the methods that can be used to estimate parameters in an area that has a small population. This study aims to estimate the value of the binary data parameter using the direct estimation method and an indirect estimation method by using the Empirical Bayes approach. To illustrate the method, we consider three conditions: direct estimator, empirical Bayes (EB) with auxiliary variables, and empirical Bayes without auxiliary variables. The smaller value of Mean Square Error is used to determine the better method. The results showed that the indirect estimation methods (EB method) gave the parameter value that was not much different from the direct estimation value. Then, the MSE values of indirect estimation with an auxiliary variable are smaller than the direct estimation method.

scholarly journals Evaluating the Approaches of Small Area Estimation Using Poverty Mapping Data

2021 ◽  
pp. 1-21
Author(s):  
Mizanur Rahman ◽  
Deluar J. Moloy ◽  
Sifat Ar Salan
Keyword(s):  
Small Area ◽  
Empirical Bayes ◽  
Small Area Estimation ◽  
Small Sample ◽  
Estimation Methods ◽  
Data Set ◽  
Area Estimation ◽  
Direct Estimation ◽  
Bivariate Correlation ◽  
Poverty Mapping

Nowadays, estimation demand in statistics is increased worldwide to seek out an estimate, or approximation, which may be a value which will be used for various purpose, albeit the input data could also be incomplete, uncertain, or unstable. The development of different estimation methods is trying to provide most accurate estimate and estimation theory deals with finding estimates with good properties. The demand of small area estimation (SAE) method has been increasing rapidly around the world because of its reliability compared to the traditional direct estimation methods, especially in the case of small sample size. This paper mainly focuses on the comparison of several indirect small area estimation methods (poststratified synthetic, SSD and EB estimates) with traditional direct estimator based on a renowned data set. Direct estimator is approximately unbiased but SSD and Post-stratified synthetic estimator is extreme biased. To cope up the problem, we conduct another model-based estimation procedure namely Empirical Bayes (EB) estimator, which is unbiased and compare them using their coefficient of variation (CV). To check the model assumption, we used Q-Q plot as well as a Histogram to confirm the normality, bivariate correlation, Akaike information criterion (AIC). JEL classification numbers: C13, C51, C51. Keywords: Small Area Estimation, Direct Estimation, Indirect Estimation, Empirical Bayes Estimator, Poverty Mapping.

scholarly journals District level child nutrition status in Bangladesh: An application of small area estimation method

2019 ◽  
Vol 53 (1) ◽  
pp. 45-61
Author(s):  
Mossamet Kamrun Nesa
Keyword(s):  
Small Area ◽  
Child Nutrition ◽  
Small Area Estimation ◽  
Estimation Method ◽  
Nutrition Status ◽  
Estimation Methods ◽  
Small Scale ◽  
Demographic Health Survey ◽  
Area Estimation ◽  
National Surveys

National level indicators of child undernutrition often hide the real scenario across a country. In order to construct a child nutrition map, accurate estimates of undernutrition are required at very small spatial scales, typically the administrative units of a country or a region within a country. Although comprehensive data on child nutrition are collected in national surveys, the small scale estimates cannot be calculated using the standard estimation methods employed in national surveys, since such methods are designed to produce national or regional level estimates, and assume large samples. Small area estimation method has been widely used to find such micro-level estimates. Due to lack of unit level data, area level small area estimation methods (e.g., Fay-Herriot method) are widely used to calculate small-scale estimates. In Bangladesh, a few works have been done to estimate district level child nutrition status. The Bangladesh Demographic Health Survey covers all districts but district wise sample sizes are very small to get consistent estimates. In this paper, Fay-Herriot Model has been developed to calculate district wise estimates with efficient mean squared error. The Bangladesh Demographic Health Survey 2011 and Population Census 2011 are utilized for this study.

scholarly journals MEMODELKAN TINGKAT PENGANGGURAN DI KOTA DENPASAR DENGAN PENDUGAAN AREA KECIL EMPIRICAL BAYES

2021 ◽  
Vol 10 (2) ◽  
pp. 81
Author(s):  
REYNALDO PANJI WICAKSONO ◽  
I KOMANG GDE SUKARSA ◽  
I PUTU EKA NILA KENCANA
Keyword(s):  
Economic Development ◽  
Unemployment Rate ◽  
Small Area ◽  
Empirical Bayes ◽  
Small Area Estimation ◽  
Economic Conditions ◽  
Small Areas ◽  
Area Estimation ◽  
Direct Estimation ◽  
Selection Of

Economic development are described by the unemployment rate. The higher unemployment rate, the weaker economic conditions. Nowadays more policies require information on small areas. The direct estimation does not provide accurate results in smaller areas. Thus the small area estimation becomes an alternative to estimate the parameters. The accuracy depends on the selection of the predictors. In 2019, the unemployment rate in Denpasar is 2,22%. The result shows that the unemployment rate in each district in Denpasar varies from 0,1% to 0,3%

scholarly journals Poisson gamma model in empirical Bayes of small area estimation (SAE)

2019 ◽  
Vol 1317 ◽  
pp. 012006
Author(s):  
Ferra Yanuar ◽  
Nadya Cindy Eka Putri ◽  
Hazmira Yozza
Keyword(s):  
Small Area ◽  
Empirical Bayes ◽  
Small Area Estimation ◽  
Gamma Model ◽  
Area Estimation

scholarly journals SMALL AREA ESTIMATION DENGAN PENDEKATAN EMPIRICAL BAYES BERBASIS MODEL BETA-BINOMIAL UNTUK MENDUGA ANGKA PENGANGGURAN DI SUMATERA BARAT

2019 ◽  
Vol 8 (1) ◽  
pp. 120
Author(s):  
Nurmaylina Zaja ◽  
Hazmira Yozza ◽  
Ferra Yanuar
Keyword(s):  
Small Area ◽  
Empirical Bayes ◽  
Small Area Estimation ◽  
Area Estimation

Penelitian ini bertujuan untuk menduga angka pengangguran di kabupaten/kota di Sumatea Barat dengan metode Small Area Estimation dengan pendekatan Empirical Bayes berbasis model Beta-Binomial. hal ini dilakukan karena informasi yang dikeluarkan oleh Badan pusat Statistik (BPS) tahun 2016 hanya angka pengangguran tingkat provinsi dan tidak tersedia data untuk tingkat kabupaten/kota. Penelitian ini menggunakan data BPS, yaitu jumlah pengangguran dan jumlah angkatan kerja di kabupaten/kota di Sumatera Barat. Penelitian ini menghasilkan nilai dugaan angka pengangguran kabupaten/kota di Sumatera Barat dengan metode langsung dan metode Empirical Bayes. Dengan demikian dapat disimpulkan bahwa penduga menggunakan metode Empirical Bayes lebih baik dari metode langsung.Diterima: Direvisi: Dipublikasikan :Kata Kunci: Small Area Estimation, Empirical Bayes, Angka Pengangguran.

scholarly journals Simple House Needs in Jember with Robust Small Area Estimation

2017 ◽  
Vol 18 (1) ◽  
pp. 1
Author(s):  
Frida Murtinasari ◽  
Alfian Futuhul Hadi ◽  
Dian Anggraeni
Keyword(s):  
Small Area ◽  
Robust Regression ◽  
Small Sample Size ◽  
Small Area Estimation ◽  
Small Sample ◽  
Estimation Methods ◽  
Linear Unbiased Prediction ◽  
Area Estimation ◽  
Best Linear Unbiased ◽  
M Estimation

SAE (Small Area Estimation) is often used by researchers, especially statisticians to estimate parameters of a subpopulation which has a small sample size. Empirical Best Linear Unbiased Prediction (EBLUP) is one of the indirect estimation methods in Small Area Estimation. The presence of outliers in the data can not guarantee that these methods yield precise predictions . Robust regression is one approach that is used in the model Small Area Estimation. Robust approach in estimating such a small area known as the Robust Small Area Estimation. Robust Small Area Estimation divided into several approaches. It calls Maximum Likelihood and M- Estimation. From the result, Robust Small Area Estimation with M-Estimation has the smallest RMSE than others. The value is 1473.7 (with outliers) and 1279.6 (without outlier). In addition the research also indicated that REBLUP with M-Estimation more robust to outliers. It causes the RMSE value with EBLUP has five times to be large with only one outlier are included in the data analysis. As for the REBLUP method is relatively more stable RMSE results.

scholarly journals Binomial Regression in Small Area Estimation Method for Estimate Proportion of Cultural Indicator

2018 ◽  
Author(s):  
Yudistira Yudistira ◽  
Anang Kurnia ◽  
Agus Mohamad Soleh
Keyword(s):  
Regression Model ◽  
Sample Size ◽  
Small Area ◽  
Small Area Estimation ◽  
Estimation Method ◽  
Alternative Methods ◽  
Area Estimation ◽  
Binomial Regression ◽  
Cultural Indicator ◽  
Sampling Survey

In sampling survey, it was necessary to have sufficient sample size in order to get accurate direct estimator about parameter, but there are many difficulties to fulfill them in practice. Small Area Estimation (SAE) is one of alternative methods to estimate parameter when sample size is not adequate. This method has been widely applied in such variation of model and many fields of research. Our research mainly focused on study how SAE method with binomial regression model is applied to obtained estimate proportion of cultural indicator, especially to estimate proportion of people who appreciate heritages and museums in each regency/city level in West Java Province. Data analysis approach used in our research with resurrected data and variables in order to be compared with previous research. The result later showed that binomial regression model could be used to estimate proportion of cultural indicator in Regency/City in Indonesia with better result than direct estimation method.

scholarly journals Adult diet in England: where is more support needed to achieve dietary recommendations?

2020 ◽  
Author(s):  
Dianna Smith ◽  
Christina Vogel ◽  
Monique Campbell ◽  
Nisreen Alwan ◽  
Graham Moon
Keyword(s):  
Urban Areas ◽  
Small Area ◽  
Vegetable Consumption ◽  
Small Area Estimation ◽  
Estimation Methods ◽  
Dietary Recommendations ◽  
Nutrition Survey ◽  
Targeted Interventions ◽  
Area Estimation ◽  
Adult Diet

Abstract Background: Small-area estimation models are regularly commissioned by public health bodies to identify areas of greater inequality and target areas for intervention in a range of behaviours and outcomes. Such local modelling has not been completed for diet consumption in England despite diet being an important predictor of health status. The study sets out whether aspects of adult diet can be modelled from previously collected data to define and evaluate area-level interventions to address obesity and ill-health.Methods: Adults aged 16 years and over living in England. Consumption of fruit, vegetables, and sugar-sweetened beverages (SSB) are modelled using small-area estimation methods in English neighbourhoods (Middle Super Output Areas [MSOA]) to identify areas where reported portions are significantly different from recommended levels of consumption. The selected aspects of diet are modelled from respondents in the National Diet and Nutrition Survey using pooled data from 2008-2016.Results: Estimates indicate that the average prevalence of adults consuming less than one portion of fruit, vegetables or 100% juice each day by MSOA is 6.9% (range of 4.3 to 14.7%, SE 0.06) and the average prevalence of drinking more than 330ml/day of SSB is 11.5% (range of 5.7 to 30.5%, SE 0.03). Credible intervals around the estimates are wider for SSB consumption. The results identify areas including regions in London and urban areas in the North of England which may be prioritised for targeted interventions to support reduced consumption of SSB and/or an increase in portions of fruit and vegetables.Conclusion: These estimates provide valuable information at a finer spatial scale than is presently feasible, allowing for within-country and locality prioritisation of resources to improve diet. Local, targeted interventions to improve fruit and vegetable consumption such as subsidies or voucher schemes should be considered where consumption of these foods is predicted to be low.

scholarly journals A COMPARISON OF SMALL AREA ESTIMATION METHODS FOR POVERTY MAPPING

2016 ◽  
Vol 17 (1) ◽  
pp. 41-66 ◽  
Author(s):  
María Guadarrama ◽  
Isabel Molina ◽  
J. N. K. Rao
Keyword(s):  
Small Area ◽  
Small Area Estimation ◽  
Estimation Methods ◽  
Area Estimation ◽  
Poverty Mapping
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