MODIFIKASI PENAKSIR PRODUK MENGGUNAKAN KOEFISIEN REGRESI ROBUST PADA SAMPEL ACAK SEDERHANA

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dc.contributor.authorRahmawati, Hasri
dc.date.accessioned2021-08-24T03:27:02Z
dc.date.available2021-08-24T03:27:02Z
dc.date.issued2020-10
dc.description.abstractThe product estimator being discussed is the product estimator for the average population in a simple random sampling using the robust regression coefficient. Robust regression being discussed uses the Least Trimmed Square (LTS) estimation method to estimate the slope coefficient. It is found that all three estimators are biased estimators. Then, the Mean Square Error (MSE) of the three estimators is compared to find the efficient estimator. It is found that an estimator that uses a combination of robust regression coefficient and kurtosis coefficient turns out to be the most efficient than other estimators when conditions are satisfied.en_US
dc.description.sponsorshipJurusan Matematika Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Riauen_US
dc.identifier.otherwahyu sari yeni
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/10136
dc.language.isoenen_US
dc.subjectProduct estimatoren_US
dc.subjectsimple random samplingen_US
dc.subjectrobust regressionen_US
dc.subjectMean Square Erroren_US
dc.subjectcoefficient of kurtosisen_US
dc.titleMODIFIKASI PENAKSIR PRODUK MENGGUNAKAN KOEFISIEN REGRESI ROBUST PADA SAMPEL ACAK SEDERHANAen_US
dc.typeArticleen_US

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