Communications for Statistical Applications and Methods最新文献

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Simulation studies to compare bayesian wavelet shrinkage methods in aggregated functional data 在聚合函数数据中比较贝叶斯小波收缩方法的仿真研究
Communications for Statistical Applications and Methods Pub Date : 2023-05-31 DOI: 10.29220/csam.2023.30.3.311
Alex Rodrigo dos Santos Sousa
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引用次数: 0
Prediction of sharp change of particulate matter in Seoul via quantile mapping 分位数映射预测首尔地区颗粒物急剧变化
Communications for Statistical Applications and Methods Pub Date : 2023-05-31 DOI: 10.29220/csam.2023.30.3.259
Jeongeun Lee, Seoncheol Park
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引用次数: 0
Bayesian Conway-Maxwell-Poisson (CMP) regression for longitudinal count data 纵向计数数据的贝叶斯康威-麦克斯韦-泊松(CMP)回归
Communications for Statistical Applications and Methods Pub Date : 2023-05-31 DOI: 10.29220/csam.2023.30.3.291
Morshed Alam, Yeongjin Gwon, Jane Meza
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引用次数: 0
Depth-Based rank test for multivariate two-sample scale problem 多元双样本尺度问题的深度秩检验
Communications for Statistical Applications and Methods Pub Date : 2023-05-31 DOI: 10.29220/csam.2023.30.3.227
Digambar Tukaram Shirke, Swapnil Dattatray Khorate
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引用次数: 0
Modifying linearly non-separable support vector machine binary classifier to account for the centroid mean vector 修改线性不可分支持向量机二值分类器,以考虑质心平均向量
Communications for Statistical Applications and Methods Pub Date : 2023-05-31 DOI: 10.29220/csam.2023.30.3.245
Mubarak Al-Shukeili, Ronald Wesonga
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引用次数: 0
Integer-Valued HAR(p) model with Poisson distribution for forecasting IPO volumes 具有泊松分布的整数HAR(p)模型预测IPO规模
Communications for Statistical Applications and Methods Pub Date : 2023-05-31 DOI: 10.29220/csam.2023.30.3.273
SeongMin Yu, Eunju Hwang
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引用次数: 0
Supervised text data augmentation method for deep neural networks 基于深度神经网络的监督文本数据增强方法
Communications for Statistical Applications and Methods Pub Date : 2023-05-31 DOI: 10.29220/csam.2023.30.3.343
Jaehwan Seol, Jieun Jung, Yeonseok Choi, Yong-Seok Choi
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引用次数: 0
Two variations of cross-distance selection algorithm in hybrid sufficient dimension reduction 混合充分降维中交叉距离选择算法的两种变体
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2023-03-31 DOI: 10.29220/csam.2023.30.2.179
J. Yoo
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引用次数: 0
GARCH-X(1; 1) model allowing a non-linear function of the variance to follow an AR(1) process GARCH-X (1;1)允许方差的非线性函数遵循AR(1)过程的模型
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2023-03-31 DOI: 10.29220/csam.2023.30.2.163
D. Nugroho, Bernadus AA Wicaksono, Lennox Larwuy
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引用次数: 1
Bias-reduced ℓ1-trend filtering 偏差减少ℓ1-趋势过滤
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2023-03-31 DOI: 10.29220/csam.2023.30.2.149
Donghyeon Yu, Johan Lim, W. Son
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引用次数: 0
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