Results 21 to 30 of about 419,209 (294)

Modelling Geographically Weighted Truncated Spline Regression Using Maximum Likelihood Estimation for Human Development Disparities

Cauchy: Jurnal Matematika Murni dan Aplikasi
A development of nonparametric truncated spline regression, Geographically Weighted Regression Spline Truncated (GWSTR) incorporates spatial effects in the modelling of nonlinear relationships between the response and predictor variables.
Laode Muhammad Saris, Henny Pramoedyo, Adji Achmad Rinaldo Fernandes   +2 more
doaj   +2 more sources

Simulasi Pemodelan Jalur Semiparametrik Truncated Spline pada Kasus Perkembangan Cashless Society

Jurnal Teknologi Informasi dan Ilmu Komputer
Simulasi merupakan suatu proses merancang model matematis dari sistem yang nyata dengan cara melakukan percobaan terhadap model menggunakan komputer.
Dea Saraswati Pramaningrum, Adji Fernandes, Atiek Iriany, Solimun, Ani Budi Astuti, Fachira Haneinanda Junianto   +5 more
doaj   +4 more sources

DEVELOPMENT OF NONPARAMETRIC PATH FUNCTION USING HYBRID TRUNCATED SPLINE AND KERNEL FOR MODELING WASTE-TO-ECONOMIC VALUE BEHAVIOR

Barekeng
Waste management remains a challenge, including in Batu City, East Java, Indonesia. Rapid population growth and economic activities in the city have resulted in a substantial increase in waste volume.
Usriatur Rohma, Adji Achmad Rinaldo Fernandes, Suci Astutik, Solimun Solimun   +3 more
doaj   +2 more sources

Spline Truncated Multivariabel pada Permodelan Nilai Ujian Nasional di Kabupaten Lombok Barat

Jurnal Matematika, 2017
Regression model is used to analyze the relationship between dependent variable and independent variable. If the regression curve form is not known, then the regression curve estimation can be done by nonparametric regression approach.
Nurul Fitriyani, Lailia Awalushaumi, Agus Kurnia   +2 more
doaj   +2 more sources

Spline estimation method in nonparametric regression using truncated spline approach

Journal of Physics: Conference Series, 2021
Abstract A parametric regression approach is used when the shape of the regression curve is known, and the nonparametric approach is used when the shape of the regression curve is unknown, the parametric regression model is still forced as a model of data patterns, it will cause inaccurate conclusions if the form of the function is not ...
D A Widyastuti, A A R Fernandes, H Pramoedyo   +2 more
openaire   +1 more source

THB-splines: The truncated basis for hierarchical splines [PDF]

Computer Aided Geometric Design, 2012
The construction of classical hierarchical B-splines can be suitably modified in order to define locally supported basis functions that form a partition of unity. The authors show that this property can be obtained by reducing the support of basis functions defined on coarse grids, according to finer levels in the hierarchy of splines.
Giannelli Carlotta, Jüttler Bert, Speleers Hendrik   +2 more
openaire   +4 more sources

REGRESSION NONPARAMETRIC SPLINE ESTIMATION ON BLOOD GLUCOSE OF INPATIENTS DIABETES MELLITUS AT SAMARINDA HOSPITAL

Barekeng, 2023
This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the ...
Ar Ruum Mia Sari, Sifriyani Sifriyani, Mohammad Nurul Huda   +2 more
doaj   +1 more source

PEMODELAN ANGKA HARAPAN HIDUP DAN ANGKA KEMATIAN BAYI DI KALIMANTAN DENGAN REGRESI NONPARAMETRIK SPLINE BIRESPON

Barekeng, 2021
Penelitian ini menggunakan model regresi nonparametrik birespon dengan pendekatan spline truncated. Model tersebut digunakan untuk menyelesaikan permasalahan analisis regresi yang bentuk kurvanya tidak diketahui.
Aprianti Boma Padatuan, Sifriyani Sifriyani, Surya Prangga   +2 more
doaj   +1 more source

Truncated T-splines: Fundamentals and methods [PDF]

Computer Methods in Applied Mechanics and Engineering, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiaodong Wei, Yongjie Zhang, Lei Liu, Thomas J.R. Hughes   +3 more
openaire   +2 more sources

Low‐rank approximation for smoothing spline via eigensystem truncation

Stat, 2021
Smoothing splines provide a powerful and flexible means for nonparametric estimation and inference. With a cubic time complexity, fitting smoothing spline models to large data is computationally prohibitive. In this paper, we use the theoretical optimal eigenspace to derive a low‐rank approximation of the smoothing spline estimates. We develop a method
Danqing Xu, Yuedong Wang
openaire   +4 more sources