A spatial obesity risk score for describing the obesogenic environment using kernel density estimation: development and parameter variation by Maximilian Präger, Christoph Kurz, Rolf Holle, Werner Maier, Michael Laxy

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Probabilistic En Route Sector Traffic Demand Prediction Based on Quantile Regression Neural Network and Kernel Density Estimation by Wen Tian, Yining Zhang, Yuchen Li, Yixing Guo

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Incipient Fault Detection in a Hydraulic System Using Canonical Variable Analysis Combined with Adaptive Kernel Density Estimation by Jinxin Wang, Shenglei Zhao, Enyuan Wang, Jiyun Zhao, Xiaofei Liu, Zhonghui Li

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Measuring Urban Renewal: A Dual Kernel Density Estimation to Assess the Intensity of Building Renovation—Case Study in Lisbon by Filipe J. S. Brandão, Ricardo M. Correia, Alexandra Paio

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Similarities between line fishing and baited stereo-video estimations of length-frequency: novel application of Kernel Density Estimates. by Timothy J Langlois, Benjamin R Fitzpatrick, David V Fairclough, Corey B Wakefield, S Alex Hesp, Dianne L McLean, Euan S Harvey, Jessica J Meeuwig

“…To assess the biases and selectivity of stereo-BRUVS and line fishing we compared the length-frequencies obtained for three commonly fished species, using a novel application of the Kernel Density Estimate (KDE) method and the established Kolmogorov-Smirnov (KS) test. …”
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Kernel Density Estimation Based Gaussian and Non-Gaussian Random Vibration Data Induction for High-Speed Train Equipment by Peng Wang, Hua Deng, Yi Min Wang, Yue Liu, Yi Zhang

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Short-term load probabilistic forecasting based on quantile regression convolutional neural network and Epanechnikov kernel density estimation by Hui He, Junting Pan, Nanyan Lu, Bo Chen, Runhai Jiao

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Nonparametric distribution of the daylight factor by Dušan Páleš, Milada Balková

Subjects: “…kernel density estimation…”
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On Inference of Overlapping Coefficients in Two Inverse Lomax Populations by Hamza Dhaker, El Hadji Deme, Salah El-Adlouni

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Spatiotemporal characteristics of elderly population's traffic accidents in Seoul using space-time cube and space-time kernel density estimation. by Youngok Kang, Nahye Cho, Serin Son

“…The purpose of this study is to analyze how the spatiotemporal characteristics of traffic accidents involving the elderly population in Seoul are changing by time period. We applied kernel density estimation and hotspot analyses to analyze the spatial characteristics of elderly people's traffic accidents, and the space-time cube, emerging hotspot, and space-time kernel density estimation analyses to analyze the spatiotemporal characteristics. …”
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Measuring the Construction Efficiency of Zero-Waste City Clusters Based on an Undesirable Super-Efficiency Model and Kernel Density Estimation Method by Xuhui Cong, Peikun Su, Liang Wang, Sai Wang, Zhipeng Qi, Jonas Šaparauskas, Jarosław Górecki, Miroslaw J. Skibniewski

“…This study uses the undesirable super-efficiency model and kernel density estimation method to measure the efficiency of zero-waste city construction in 16 prefecture-level cities in Shandong Province and analyze their spatial and temporal differences. …”
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Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions by Parviz Ghaderi, Parviz Ghaderi, Marjan Nosouhi, Mislav Jordanic, Hamid Reza Marateb, Hamid Reza Marateb, Miguel Angel Mañanas, Miguel Angel Mañanas, Dario Farina

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Automated differentiation of Alzheimer’s condition using Kernel Density Estimation based texture analysis of single slice brain MR images by Veluppal Amrutha, Sadhukhan Deboleena, Gopinath Venugopal, Swaminathan Ramakrishnan

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Hybrid methodology for modeling short-term wind power generation using conditional Kernel density estimation and singular spectrum analysis by Soraida Aguilar-Vargas, Reinaldo Castro-Souza, José Francisco Pessanha, Fernando Luiz Cyrino-Oliveira

“…To achieve accurate probabilistic forecast of wind output, it is developed a hybrid methodology using a nonparametric techniques known as SSA (Singular Spectrum Analysis) and (CKDE) Conditional Kernel Density Estimation. SSA is employed to forecast wind speed and CKDE to obtain probabilistic forecasts of wind energy, based on the fact that wind power generation has a nonlinear relation with the wind speed and both are random variables distributed according to a joint density function. …”
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A Berry-Esseen type bound for the kernel density estimator based on a weakly dependent and randomly left truncated data by Petros Asghari, Vahid Fakoor

“…In this paper we are interested in deriving the asymptotic normality as well as a Berry-Esseen type bound for the kernel density estimator of left truncated and weakly dependent data.…”
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Research on measurement and disequilibrium of manufacturing digital transformation: Based on the text mining data of A-share listed companies by Chong Li, Guoqiong Long, Shuai Li

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A Multivariate Kernel Approach to Forecasting the Variance Covariance of Stock Market Returns by Ralf Becker, Adam Clements, Robert O'Neill

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A diffusion-based kernel density estimator (diffKDE, version 1) with optimal bandwidth approximation for the analysis of data in geoscience and ecological research by M.-T. Pelz, M.-T. Pelz, M. Schartau, C. J. Somes, V. Lampe, T. Slawig

“…A common tool for such non-parametric estimation is a kernel density estimator (KDE). Existing KDEs are valuable but problematic because of the difficulty of objectively specifying optimal bandwidths for the individual kernels. …”
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Using Twitter Data to Monitor Natural Disaster Social Dynamics: A Recurrent Neural Network Approach with Word Embeddings and Kernel Density Estimation by Aldo Hernandez-Suarez, Gabriel Sanchez-Perez, Karina Toscano-Medina, Hector Perez-Meana, Jose Portillo-Portillo, Victor Sanchez, Luis Javier García Villalba

“…The resulting labeled words are joined to coherently form a toponym, which is geocoded and scored by a Kernel Density Estimation function. At the end of the process, the scored data are presented graphically to depict areas in which the majority of tweets reporting topics related to a natural disaster are concentrated. …”
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PCA-based Hotelling's T2 chart with fast minimum covariance determinant (FMCD) estimator and kernel density estimation (KDE) for network intrusion detection by Muhammad Mashuri, Muhammad Mashuri, Muhammad Ahsan, Muhammad Ahsan, Lee, Muhammad Hisyam, Prastyo, Dedy Dwi, Wibawati, Wibawati

“…To solve this issue, the Kernel Density Estimation (KDE) procedure is applied to obtain an optimum control limit. …”