Results 1 to 10 of about 124,056 (156)

Cross-Validation Model Averaging for Generalized Functional Linear Model [PDF]

open access: yesEconometrics, 2020
Functional data is a common and important type in econometrics and has been easier and easier to collect in the big data era. To improve estimation accuracy and reduce forecast risks with functional data, in this paper, we propose a novel cross ...
Haili Zhang, Guohua Zou
doaj   +5 more sources

Determination of the best knot and bandwidth in geographically weighted truncated spline nonparametric regression using generalized cross validation [PDF]

open access: yesMethodsX, 2023
This study proposes the development of nonparametric regression for data containing spatial heterogeneity with local parameter estimates for each observation location.
Robiansyah Putra   +2 more
doaj   +2 more sources

Determination of the best multivariate adaptive geographically weighted generalized Poisson regression splines model employing generalized cross-validation in dengue fever cases [PDF]

open access: yesMethodsX, 2023
This article constructs a new model based on multivariate adaptive generalized Poisson regression splines (MAGPRS) and geographically weighted generalized Poisson regression (GWGPR), which is known as multivariate adaptive geographically weighted ...
Riry Sriningsih   +2 more
doaj   +2 more sources

The generalized cross validation filter [PDF]

open access: yesAutomatica, 2018
Generalized cross validation (GCV) is one of the most important approaches used to estimate parameters in the context of inverse problems and regularization techniques. A notable example is the determination of the smoothness parameter in splines. When the data are generated by a state space model, like in the spline case, efficient algorithms are ...
Giulio Bottegal, Gianluigi Pillonetto
exaly   +5 more sources

Improved Generalized Cross-Validation and Unbiased Predictive Risk Estimator Methods Using the RGSVD: Application to Inversion of Potential Field Data

open access: yesApplied Sciences, 2021
The inversion of potential field data has widely utilized the generalized cross-validation (GCV) and the unbiased predictive risk estimator (UPRE) methods to determine the regularization parameter.
Yuan Fang   +3 more
doaj   +3 more sources

Generalized cross validation for ℓp-ℓq minimization [PDF]

open access: yesNumerical Algorithms, 2021
AbstractDiscrete ill-posed inverse problems arise in various areas of science and engineering. The presence of noise in the data often makes it difficult to compute an accurate approximate solution. To reduce the sensitivity of the computed solution to the noise, one replaces the original problem by a nearby well-posed minimization problem, whose ...
Buccini A., Reichel L.
openaire   +3 more sources

MODELING OF LOCAL POLYNOMIAL KERNEL NONPARAMETRIC REGRESSION FOR COVID DAILY CASES IN SEMARANG CITY, INDONESIA

open access: yesMedia Statistika, 2022
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which was recently discovered.
Tiani Wahyu Utami, Aisyah Lahdji
doaj   +1 more source

Multi-label Classification Using Vector Generalized Additive Model via Cross-Validation

open access: yesJournal of ICT, 2023
Multi-label classification is a unique challenge in machine learning designed for two targets with each containing one or multiple classes. This problem can be resolved using several methods, including the classification of the targets individually or ...
Amri Muhaimin   +2 more
doaj   +1 more source

Poverty in Central Java using Multivariate Adaptive Regression Splines and Bootstrap Aggregating Multivariate Adaptive Regression Splines

open access: yesCauchy: Jurnal Matematika Murni dan Aplikasi, 2021
Population poverty is one of the serious problems in Indonesia. The percentage of population poverty used as a means for a statistical instrument to be guidelines to create standard policies and evaluations to reduce poverty. The aims of the research are
Ria Dhea Layla Nur Karisma   +2 more
doaj   +1 more source

Smoothing and Differentiation of Kinematic Data Using Functional Data Analysis Approach: An Application of Automatic and Subjective Methods

open access: yesApplied Sciences, 2020
Smoothing is one of the fundamental procedures in functional data analysis (FDA). The smoothing parameter λ influences data smoothness and fitting, which is governed by selecting automatic methods, namely, cross-validation (CV) and generalized ...
Muhammad Athif Mat Zin   +3 more
doaj   +1 more source

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