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pro vyhledávání: '"Chen, Song Xi"'
Autor:
Yan, Han, Chen, Song Xi
We consider statistical inference for parameters defined by general estimating equations under the covariate shift transfer learning. Different from the commonly used density ratio weighting approach, we undertake a set of formulations to make the st
Externí odkaz:
http://arxiv.org/abs/2410.04398
Autor:
Yan, Han, Chen, Song Xi
Segmented regression models offer model flexibility and interpretability as compared to the global parametric and the nonparametric models, and yet are challenging in both estimation and inference. We consider a four-regime segmented model for tempor
Externí odkaz:
http://arxiv.org/abs/2410.04384
We provide a review on the "optimal fingerprinting" approach as summarized in Allen and Tett (1999) from a point view of statistical inference in light of the recent criticism of McKitrick (2021). Our review finds that the "optimal fingerprinting" ap
Externí odkaz:
http://arxiv.org/abs/2205.10508
Autor:
Zhang, Huiming, Chen, Song Xi
Publikováno v:
Communications in Mathematical Research. 37(1), 1-85 (2021)
This paper gives a review of concentration inequalities which are widely employed in non-asymptotical analyses of mathematical statistics in a wide range of settings, from distribution-free to distribution-dependent, from sub-Gaussian to sub-exponent
Externí odkaz:
http://arxiv.org/abs/2011.02258
Akademický článek
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This paper provides a thorough analysis on the dynamic structures and predictability of China's Consumer Price Index (CPI-CN), with a comparison to those of the United States. Despite the differences in the two leading economies, both series can be w
Externí odkaz:
http://arxiv.org/abs/1910.13301
We consider testing the equality of two high-dimensional covariance matrices by carrying out a multi-level thresholding procedure, which is designed to detect sparse and faint differences between the covariances. A novel U-statistic composition is de
Externí odkaz:
http://arxiv.org/abs/1910.13074
Publikováno v:
In Journal of Econometrics August 2023 235(2):1337-1354
Matrix completion is a modern missing data problem where both the missing structure and the underlying parameter are high dimensional. Although missing structure is a key component to any missing data problems, existing matrix completion methods ofte
Externí odkaz:
http://arxiv.org/abs/1812.07813
Publikováno v:
Climate Dynamics. Feb2024, Vol. 62 Issue 2, p1439-1446. 8p.