BibTex Citation Data :
@article{J.Gauss10936, author = {Bitoria Niashinta and Dwi Ispriyanti and Abdul Hoyyi}, title = {PENDUGAAN AREA KECIL TERHADAP PENGELUARAN PER KAPITA DI KABUPATEN SRAGEN DENGAN PENDEKATAN KERNEL}, journal = {Jurnal Gaussian}, volume = {5}, number = {1}, year = {2016}, keywords = {Direct Estimation, Small Area Estimation (SAE), Kernel Gaussian}, abstract = { Data of Social Survey and Economic National is a relatively small sample of data, so that data is called small area. Estimation of parameter in small area can be done in two ways, there are direct estimation and indirect estimation. Direct estimation is unbias estimation but give a high variance because from small sample of data. The technique that use to increase efectivity of sample size is indirect estimation or called Small Area Estimation (SAE). SAE is done by adding auxiliary variable. on estimating parameter. Assumed that auxiliary variable has a linear correlation with the direct estimation. If that assumption is incomplete, use an nonparametric approaching. This research is using Kernel Gaussian approaching to build a correlation between direct estimation which expenditure per capita and auxiliary variable which population density. Evaluation of estimation result is done by comparing the value of direct estimation variance with the value of indirect estimation variance using Kernel Gaussian approaching. The result of parameter estimation which approached by SAE is the best estimation, because it produce the small value of variance that is 5,31275, while the value of direct estimator variance is 6,380522. Keywords : Direct Estimation, Small Area Estimation (SAE), Kernel Gaussian }, issn = {2339-2541}, pages = {71--80} doi = {10.14710/j.gauss.5.1.71-80}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10936} }
Refworks Citation Data :
Data of Social Survey and Economic National is a relatively small sample of data, so that data is called small area. Estimation of parameter in small area can be done in two ways, there are direct estimation and indirect estimation. Direct estimation is unbias estimation but give a high variance because from small sample of data. The technique that use to increase efectivity of sample size is indirect estimation or called Small Area Estimation (SAE). SAE is done by adding auxiliary variable. on estimating parameter. Assumed that auxiliary variable has a linear correlation with the direct estimation. If that assumption is incomplete, use an nonparametric approaching. This research is using Kernel Gaussian approaching to build a correlation between direct estimation which expenditure per capita and auxiliary variable which population density. Evaluation of estimation result is done by comparing the value of direct estimation variance with the value of indirect estimation variance using Kernel Gaussian approaching. The result of parameter estimation which approached by SAE is the best estimation, because it produce the small value of variance that is 5,31275, while the value of direct estimator variance is 6,380522.
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