Distribution estimation for noisy data via density deconvolution is a notoriously difficult problem, especially for typical noise distributions like Gaussian. We develop a density deconvolution estima

DataCite Commons2020-08-26 更新90

SHAPES

机器学习

密度估计

该数据集是一个用于概念验证实验的低维数据集，它展示了将两个连续协变量与一个分类类别标签结合的方法。边界并不总是清晰，这表明通过增加树的数量或扩大训练集，还有改进的空间。该数据集包含了2000个样本，其任务是进行密度估计和生成建模。

arXiv70

Partition Weighted Approach for Estimating the Marginal Posterior Density with Applications

贝叶斯分析

密度估计

The computation of marginal posterior density in Bayesian analysis is essential in that it can provide complete information about parameters of interest. Furthermore, the marginal posterior density ca

tandf.figshare.com2023-05-31 更新110

Covariate Information Matrix for Sufficient Dimension Reduction

充分降维

密度估计

Building upon recent research on the applications of the density information matrix, we develop a tool for sufficient dimension reduction (SDR) in regression problems called covariate information matr

DataCite Commons2022-02-10 更新80

OCACS 2021 Census Tract Population Density

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