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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Matematika E-Jurnal Matematika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI EIGEN MATHEMATICS JOURNAL Jurnal Gema Ngabdi Jurnal Varian Jurnal Pengabdian Masyarakat Sains Indonesia (Indonesian Journal Of Science Community Services) Journal of Mathematics: Theory and Applications Prosiding Konferensi Nasional PKM-CSR Kajian Sastra Nusantara Linggau ( KASTRAL) Jurnal Karya Pengabdian Teknik Mesin Jurnal Pepadu Jurnal Intelek Insan Cendikia Indonesian Journal of Islamic Religious Education (INJIRE) Indonesian Science Education Journal (ISEJ) AL-Ikhtiar : Jurnal Studi Islam
Nurul Fitriyani
Department Of Mathematics, Faculty Of Mathematics And Sciences, University Of Mataram Mataram, Indonesia
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Journal : E-Jurnal Matematika

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CURVE ESTIMATION AND ESTIMATOR PROPERTIES OF THE NONPARAMETRIC REGRESSION TRUNCATED SPLINE WITH A MATRIX APPROACH NURUL FITRIYANI; I NYOMAN BUDIANTARA
E-Jurnal Matematika Vol 11 No 1 (2022)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2022.v11.i01.p362

Abstract

Regression analysis is one of the statistical analyses used to estimate the relationship between the predictor and the response variable. Data are given in pairs, and the relationship between the predictor and the response variable was assumed to follow a nonparametric regression model. This model is flexible in estimating the curve when a typical data pattern does not follow a specific pattern. The nonparametric regression curve was approached by using the truncated spline function with several knots. The truncated spline estimator in nonparametric regression is linear in the observation. It is highly dependent on the knot points. The regression model's random error is assumed to have an independent normal distribution with zero mean and equal variance. The truncated spline's curve estimate was obtained by minimizing the error model through the least squared optimization method. The nonparametric regression truncated spline's estimator properties are linear, unbiased, and if the error is normally distributed, the estimator is normally distributed.
Co-Authors Abdillah Rizki Tanjung Agus Kurnia Akhmed Syarifatul Raflus Alfira Sofia Rahayu Amalia Chairunissa Atma Utami Sawitri Baiq Urfa Justitiaski Bidayani Bidayani Dalmeri Deni Pratiwi Desy Komalasari Dini Wijayanti Ema Syaidah Ena Setiawana Erry Esa Aprilliansyah Harsyiah, Lisa Himayati Himayati Husnul Arini I Gde Ekaputra Gunartha I Gede Ekaputra Gunartha I Nyoman Budiantara Jamaluddin Joji Ardian Pembargi Jurnal Pepadu Jusmawati Jusmawati Komarudin Lailia Awalushaumi Lalu Abd Azis Mursy Moudy Puspita Ayudhiah Muhamad Aditio Apriesta Suharto Muhammad Rijal Alfian Muhammad Rizaldi Muhammad Sopian Sauri Mustika Hadijati Ni Luh Putu Dewi Wikayanti Ni Wayan Switrayni Nisa Syahrani Nurhafizah Oca Qurratul Aini Riski Aprilia Rosanti W. ahidatussolihah Salwa Salwa Sapurah Sapurah Siti Wulandari Sri Wati Agustini Syamsul Bahri Ulfa Destiarina