Results 21 to 30 of about 205,425 (288)

Choice of Smoothing Parameter for Kernel Type Ridge Estimators in Semiparametric Regression Models

Revstat Statistical Journal, 2021
This paper concerns kernel-type ridge estimators of parameters in a semiparametric model. These estimators are a generalization of the well-known Speckman’s approach based on kernel smoothing method. The most important factor in achieving this smoothing
Ersin Yilmaz , Bahadir Yuzbasi , Dursun Aydin   +2 more
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Cross-Validation, Information Theory, or Maximum Likelihood? A Comparison of Tuning Methods for Penalized Splines

Stats, 2021
Functional data analysis techniques, such as penalized splines, have become common tools used in a variety of applied research settings. Penalized spline estimators are frequently used in applied research to estimate unknown functions from noisy data ...
Lauren N. Berry, Nathaniel E. Helwig
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A Comparison of the Smoothing Constant Values Among Exponential Smoothing Methods in Commodity Prices Forecasting

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022
Commodity prices forecasting is one of the business functions to estimate future demand based on past data trend. This study aims to implement a trial and error technique of the constant (alpha α) value in the exponential smoothing method.
Hazriani Hazriani, Yuyun, Mashur Razak
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Two-dimensional NMR inversion based on fast norm smoothing method

Energy Geoscience, 2022
Two-dimensional (2D) nuclear magnetic resonance (NMR) inversion operates with massive echo train data and is an ill-posed problem. It is very important to select a suitable inversion method for the 2D NMR data processing. In this study, we propose a fast,
Youlong Zou, Jun Li, Song Hu, Junlei Su, Mi Liu, Jun Zhang   +5 more
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On the Number of Independent Pieces of Information in a Functional Linear Model with a Scalar Response

Stats, 2020
In a functional linear model (FLM) with scalar response, the parameter curve quantifies the relationship between a functional explanatory variable and a scalar response.
Eduardo L. Montoya
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One Value of Smoothing Parameter vs Interval of Smoothing Parameter Values in Kernel Density Estimation

Acta Universitatis Lodziensis. Folia Oeconomica, 2017
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.
Aleksandra Katarzyna Baszczyńska
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Comparison of Remote Sensing Time-Series Smoothing Methods for Grassland Spring Phenology Extraction on the Qinghai–Tibetan Plateau

Remote Sensing, 2020
Accurate evaluation of start of season (SOS) changes is essential to assess the ecosystem’s response to climate change. Smoothing method is an understudied factor that can lead to great uncertainties in SOS extraction, and the applicable situation for ...
Nan Li, Pei Zhan, Yaozhong Pan, Xiufang Zhu, Muyi Li, Dujuan Zhang   +5 more
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Resistant Nonparametric Smoothing with S-PLUS

Journal of Statistical Software, 2004
In this paper we introduce and illustrate the use of an S-PLUS set of functions to fit M-type smoothing splines with the smoothing parameter chosen by a robust criterion (either a robust version of cross-validation or a robust version of Mallows's Cp ...
Eva Cantoni
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Robust smoothing of one‐dimensional data with missing and/or outlier values

IET Signal Processing, 2021
Penalized least squares (PLS) is a popular data smoothing technique. However, existing PLS smoothing algorithms behave as low‐pass filters (LPF), and, hence, they may introduce distortions to bandpass signals.
Nasser Mourad
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Small-Signal Stability Modeling for MMC-Based DC Grids With Voltage Slope Control and Influence Analysis of Parameters

IEEE Access, 2022
In the flexible DC grids, selections of slope coefficients in system level controls and designs of smoothing reactors have a crucial influence on the system stability.
Hui Li, Xinqiao Fan, Sijia Liu
doaj   +1 more source