ESTIMASI MODEL REGRESI SEMIPARAMETRIK DISKRIT

• Main Authors: , Baiq Diah Fitasari, , Prof. Dr. Sri Haryatmi, M.Sc.
• Format: Theses and Dissertations NonPeerReviewed
• Published: [Yogyakarta] : Universitas Gadjah Mada 2014
• Subjects: ETD
• Online Access: https://repository.ugm.ac.id/133813/; http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=74651
• Institution: Universitas Gadjah Mada

Approaches that are used to estimate the regression function are parametric regression model approaching and nonparametric regression model approaching. Semiparametric regression is association of parametric regression and nonparametric regression. Semiparametric regression is used if the relation pattern between independent variables and dependent variables has the known pattern and also has the unknown pattern. Estimating the unknown regression approaching and in this case is using the Nadaraya-Watson estimator. Semiparametric estimator is better than nonparametric estimator for the data which have the unknown relation pattern between dependent and independent variable and also has the unknown relation pattern between dependent and independent variable by using the MSE and AIC value.