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基于受扰直方图数据的间接密度估计带宽选择AI 解读

Motivated by a number of practical applications, we consider a class of indirect nonparametric density estimation problems in which the observed data consist of a histogram of binned empirically corrected counts. Due to variability in the process of correction, the histogram cannot be modeled in terms of simple scaled Poisson statistics. This departure necessitates the development of a new methodology for bandwidth selection. A variant of the method of unbiased risk…

基于受扰直方图数据的间接密度估计带宽选择AI 解读

Motivated by a number of practical applications, we consider a class of indirect nonparametric density estimation problems in which the observed data consist of a histogram of binned empirically corrected counts. Due to variability in the process of correction, the histogram cannot be modeled in terms of simple scaled Poisson statistics. This departure necessitates the development of a new methodology for bandwidth selection. A variant of the method of unbiased risk…

基于惩罚 Whittle 似然的非参数谱密度估计AI 解读

The penalized likelihood approach is not well developed in time series analysis, even though it has been applied successfully in a number of nonparametric function estimation problems. Chow and Grenander proposed a penalized likelihood-type approach to the nonparametric estimation of the spectral density of Gaussian processes. In this article this estimator is extended to more general stationary processes, its practical implementation is developed in some detail, and some…

通过层析成像进行多维密度估计AI 解读

SUMMARY The paper explores the application of the filtered backprojection algorithm of computerized tomography to statistical smoothing of multidimensional densities. The method makes use of automated one-dimensional density smoothers to obtain an automated smoothed multidimensional density. No structural assumptions such as additivity or log-additivity are used. An important computational aspect of this method is its inherently parallel structure. We demonstrate linear…