Results 51 to 60 of about 1,589,421 (354)
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2004 Kernel smoothers belong to the most popular nonparametric functional estimates. They provide a simple way of finding structure in data. Kernel smoothing can be very well applied on the regression model.
Jitka Poměnková
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Understanding Exponential Smoothing Via Kernel Regression
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1999 Summary Exponential smoothing is the most common model-free means of forecasting a future realization of a time series. It requires the specification of a smoothing factor which is usually chosen from the data to minimize the average squared residual of previous one-step-ahead forecasts.
Gijbels, I., Pope, A., Wand, M. P.
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A test for model specification of diffusion processes
, 2008 We propose a test for model specification of a parametric diffusion process based on a kernel estimation of the transitional density of the process. The empirical likelihood is used to formulate a statistic, for each kernel smoothing bandwidth, which is ...
Chen, Song Xi +2 more
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Smoothing Module for Optimization Cranium Segmentation Using 3D Slicer
International Journal of Applied Sciences and Smart Technologies, 2023 Anatomy is the most essential course in health and medical education to study parts of human body and also the function of it. Cadaver is a media used by medical student to study anatomical subject.
Gilang Argya Dyaksa +4 more
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, 2020 Image acquisition and segmentation are likely to introduce noise. Further image processing such as image registration and parameterization can introduce additional noise. It is thus imperative to reduce noise measurements and boost signal. In order to increase the signal-to-noise ratio (SNR) and smoothness of data required for the subsequent random ...
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Network Localization of Fatigue in Multiple Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo +12 more
wiley +1 more source
A new method of kernel-smoothing estimation of the ROC curve
, 2016 The receiver operating characteristic (ROC) curve is a popular graphical tool for describing the accuracy of a diagnostic test. Based on the idea of estimating the ROC curve as a distribution function, we propose a new kernel smoothing estimator of the ...
Michal Pulit
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
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International Journal of Adaptive Control and Signal Processing, EarlyView.This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
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ESTIMATOR KERNEL DALAM MODEL REGRESI NONPARAMETRIK
Jurnal Matematika, 2012 Analisis regresi nonparametrik merupakan metode pendugaan kurva regresi yang digunakan jika tidak ada informasi sebelumnya te,ntang benttrk kurva regresi atau tidak terikat pada asumsi bentuk fungsi tertentu.
I Komang Gede Sukarsa +1 more
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