REGRESI NONPARAMETRIK KERNEL ADJUSTED
Nadaraya watson�s kernel adjusted regression estimator is an estimator that whose kernel is taken from the family of scale-location associated with the classical kernel density estimator. Based on these estimator, it can be obtained optimal bandwith and scale parameter. This estimator gives a bett...
محفوظ في:
| المؤلفون الرئيسيون: | , |
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| التنسيق: | Theses and Dissertations NonPeerReviewed |
| منشور في: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://repository.ugm.ac.id/133812/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=74649 |
| الوسوم: |
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| الملخص: | Nadaraya watsonâ��s kernel adjusted regression estimator is an estimator that
whose kernel is taken from the family of scale-location associated with the classical
kernel density estimator. Based on these estimator, it can be obtained optimal bandwith
and scale parameter. This estimator gives a better estimation results compared
with Naradaya Watson�s clasical kernel regression estimator. This is proven by the
small grade MSE which is given by this estimator. |
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