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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI UNEJ e-Proceeding BAREKENG: Jurnal Ilmu Matematika dan Terapan SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Kreativitas PKM ESTIMASI: Journal of Statistics and Its Application Journal of Social Outreach Journal of Research Applications in Community Services Eksponensial STATISTIKA
Darnah, Darnah
Mulawarman University
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Journal : JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI

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Menentukan Model Terbaik dalam Regresi Poisson dengan Menggunakan Koefisien Determinasi Darnah Darnah
Jurnal Matematika, Statistika dan Komputasi Vol. 6 No. 2: January 2010
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (569.266 KB) | DOI: 10.20956/jmsk.v6i2.3355

Abstract

Pemodelan Pemodelan Regresi Nonparametrik Berdasarkan Estimator Spline Truncated pada Data Simulasi Ghony N Nurhuda; Wasono Wasono; Darnah Andi Nohe
Jurnal Matematika, Statistika dan Komputasi Vol. 19 No. 1 (2022): SEPTEMBER, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v19i1.21534

Abstract

Regression analysis is one of the statistical analysis used to estimate the pattern of the relationship between predictor variables and response variables . In general, the approach to estimating the regression function is the parametric regression, the nonparametric regression and the semiparametric regression. The approach with parametric regression is used if the shape of the regression curve is assumed to follow a certain pattern such as linear, quadratic, cubic and so on, but in fact there is an unknown pattern of relationship between predictor variables and response variables, so nonparametric regression is used. Then the combination of parametric and nonparametric regression is semiparametric regression. One of the well-known nonparametric regression estimators is the spline truncated. This study was conducted by simulating the relationship pattern of the response variable and the predictor variable that not have specific pattern by following a trigonometric function that formed a regression curve with a standard deviation of 0,05 and 0,25 which formed a different distribution of data, then will be approached with parametric regression (linear, quadratic, cubic) and nonparametric regression (spline truncated linear). Based on the coefficient of determination of each standard deviation, it will shows that the nonparametric regression approach has high flexibility so that it is able to adjust the form of regression curve estimation by itself
Co-Authors Alfina Damayanti Chairunnisa, Niken Harel Dani, Andrea Tri Rian Dini Elizabeth Eka Nur Amaliah Fauziyah, Meirinda Ghony N Nurhuda Ika Purnamasari Khairun Nida Kriesniati, Prastika Krisna Rendi Awalludin M. Fathurahman M. RIZKY RAMADHAN Meiliyani Siringoringo Memi Nor Hayati Memi Norhayati Nadia Serena Ratna Kusuma, Ratna Rito Goejantoro, Rito Rut Esra Samsurianto Samsurianto Sekar Nur Utami Septian, Rama Sifriyani, Sifriyani Surya Prangga Syaripuddin Syaripuddin Wasono Wasono Yuniarti, Desi