Results 11 to 20 of about 3,774,080 (285)
Fault Diagnosis Method of Wind Turbine Pitch Angle Based on PCA-KNN Fusion Algorithm
With regard to the four main fault types of the pitch angle of a wind turbine pitch system and the data analysis of the wind turbine, an identification method of abnormal pitch angles of a wind turbine is proposed, depending on nonparametric kernel ...
Xi CHEN +5 more
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At the heart of many ICA techniques is a nonparametric estimate of an information measure, usually via nonparametric density estimation, for example, kernel density estimation.
Julian Sorensen
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Beta Kernel Estimator for a Cumulative Distribution Function with Bounded Support [PDF]
Kernel estimation of the cumulative distribution function (CDF), when the support of the data is bounded, suffers from bias at the boundaries. To solve this problem, we introduce a new estimator for the CDF with support (0,1) based on the beta kernel ...
Behzad Mansouri +2 more
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Bootstrap methods are used for bandwidth selection in: (1) nonparametric kernel density estimation with dependent data (smoothed stationary bootstrap and smoothed moving blocks bootstrap), and (2) nonparametric kernel hazard rate estimation (smoothed ...
Inés Barbeito, Ricardo Cao
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Using conditional kernel density estimation for wind power density forecasting [PDF]
Of the various renewable energy resources, wind power is widely recognized as one of the most promising. The management of wind farms and electricity systems can benefit greatly from the availability of estimates of the probability distribution of wind ...
Jeon, Jooyoung, Taylor, James
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Research of comparative analysis of nonparametric density estimation by applying Monte Carlo method
This paper presents nonparametric statistical estimation of distribution density. The Monte Carlo method is used to show the effects of kernel function for multimodal kernel density estimation.
Indrė Drulytė, Tomas Ruzgas
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Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors
This paper develops a sampling algorithm for bandwidth estimation in a nonparametric regression model with continuous and discrete regressors under an unknown error density.
Xibin Zhang +2 more
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Nonparametric gamma kernel estimators of density derivatives on positive semi-axis [PDF]
We consider nonparametric estimation of the derivative of a probability density function with the bounded support on $[0,\infty)$. Estimates are looked up in the class of estimates with asymmetric gamma kernel functions. The use of gamma kernels is due to the fact they are nonnegative, change their shape depending on the position on the semi-axis and ...
Alexander V. Dobrovidov +1 more
openaire +3 more sources
NPCirc: An R Package for Nonparametric Circular Methods
Nonparametric density and regression estimation methods for circular data are included in the R package NPCirc. Specifically, a circular kernel density estimation procedure is provided, jointly with different alternatives for choosing the smoothing ...
María Oliveira +2 more
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The adaptive gamma-BSPE kernel density estimation for nonnegative heavy-tailed data
In this work, we consider the nonparametric estimation of the probability density function for nonnegative heavy-tailed (HT) data. The objective is first to propose a new estimator that will combine two regions of observations (high and low density ...
Yasmina ZIANE +2 more
doaj +4 more sources

