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Asymptotic normality of kernel type density estimators for random fieldsKernel type density estimators are studied for random fields. It is proved that the estimators
Asymptotic normality of kernel type density estimators for random fieldsKernel type density estimators are studied for random fields. It is proved that the estimators
USING RICHARDSON EXTRAPOLATION TO IMPROVE THE ACCURACY OF PROCESSING AND ANALYZING EMPIRICAL DATA to improve
the accuracy of constructing a probability density function and estimating its error. The method
Сравнение методов извлечения осевых траекторий в задаче обновления карт principal curve, b-spline и kernel density estimation. Эти методы сравниваются с помощью метрик
точности
Modification of Nonparametric Probability Density Estimation of Parzen's Type with Implicitly Given form of Kernel FunctionThe new nonparametric probability density estimation based on use of the smoothing operator
Estimating smoothness and optimal bandwidth for probability density functionsThe properties of non-parametric kernel estimators for probability density function from two
Adaptive algorithm of classifcation on the missing data. Computational procedures are based on non-parametric estimation, are given their settings and the results
Improving the Accuracy of the Probability Density Function Estimation for increasing
accuracy. We prove the estimates of the accuracy of the probability density function and its
Improving the Accuracy of the Probability Density Function Estimation for increasing
accuracy. We prove the estimates of the accuracy of the probability density function and its
Оптимальное ядерное оценивание плотности методом статистического моделирования при случайном цензурировании наблюденийOptimal kernel density estimation by statistical modeling with random censoring of observations
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