Direct Determination of Smoothing Parameter for Penalized Spline Regression [PDF]
Journal of Probability and Statistics, 2014 Penalized spline estimator is one of the useful smoothing methods. To construct the estimator, having goodness of fit and smoothness, the smoothing parameter should be appropriately selected. The purpose of this paper is to select the smoothing parameter
Takuma Yoshida
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Histogram Filter with Smoothing Parameter Setting
Доклады Белорусского государственного университета информатики и радиоэлектроники, 2023 A histogram filter with smoothing parameter settings is discussed in the article. The histogram filter can be effectively applied in the problems of identification (recognition) of distribution laws for small amounts of data.
A. V. Ausiannikau, V. M. Kozel
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One Value of Smoothing Parameter vs Interval of Smoothing Parameter Values in Kernel Density Estimation [PDF]
Acta Universitatis Lodziensis. Folia Oeconomica, 2018 Ad hoc methods in the choice of smoothing parameter in kernel density estimation, although often used in practice due to their simplicity and hence the calculated efficiency, are characterized by quite big error. The value of the smoothing parameter chosen by Silverman method is close to optimal value only when the density function in population is ...
Aleksandra Katarzyna Baszczyńska
openaire +5 more sources
Reservoir characterization and porosity classification using probabilistic neural network (PNN) based on single and multi-smoothing parameters [PDF]
International Journal of Mining and Geo-Engineering, 2022 A probabilistic neural network (PNN) is a feed-forward neural network using a smoothing parameter. We used the PNN algorithm based on single and multi-smoothing parameters for multi-dimensional data classification.
Masood Lashkari Ahangarani +2 more
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Smoothing parameter selection in Nadaraya-Watson kernel nonparametric regression using nature-inspired algorithm optimization [PDF]
المجلة العراقية للعلوم الاحصائية, 2020 In the context of Nadaraya-Watson kernel nonparametric regression, the curve estimation is fully depending on the smoothing parameter. At this point, the nature-inspired algorithms can be used as an alternative tool to find the optimal selection. In this
Zinah Basheer, Zakariya Algamal
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Analisis Error Terhadap Peramalan Data Penjualan
Techno.Com, 2021 Tujuan penelitian ini membahas tentang peramalan permintaan lampu LED bermerk Sanyo. Penelitian ini menggunakan metode Moving Average dan Exponential Smoothing.
Alyauma Hajjah, Yulvia Nora Marlim
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Use of Two Smoothing Parameters in Penalized Spline Estimator for Bi-variate Predictor Non-parametric Regression Model [PDF]
Journal of Sciences, Islamic Republic of Iran, 2020 Penalized spline criteria involve the function of goodness of fit and penalty, which in the penalty function contains smoothing parameters. It serves to control the smoothness of the curve that works simultaneously with point knots and spline degree. The
Anna Islamiyati
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Spline estimator and its asymptotic properties in multiresponse nonparametric regression model [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2020 In applications, we often meet the problem where more than one response variable is observed at several values of predictor variables, and these responses are correlated with each other.
Budi Lestari +2 more
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PREDIKSI JUMLAH CALON PESERTA DIDIK BARU MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING DARI BROWN
Jurnal Lebesgue, 2020 Peramalan data statistika memerlukan kesesuaian pola data dengan metode peramalan yang digunakan. Tujuan penelitian ini yaitu memprediksi jumlah mahasiswa baru pada tahun ajaran baru menggunakan metode Double Exponential Smoothing satu parameter dari ...
Aden, Anggela Supriyanti
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Stochastic Smoothing Methods for Nonsmooth Global Optimization
Кібернетика та комп'ютерні технології, 2020 . The paper presents the results of testing the stochastic smoothing method for global optimization of a multiextremal function in a convex feasible subset of Euclidean space.
V.I. Norkin
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