Zobrazeno 1 - 10
of 233
pro vyhledávání: '"Liu Shishi"'
Autor:
Cao Shunqing, Liu Shishi
Publikováno v:
Comparative Literature: East & West, Vol 7, Iss 2, Pp 93-112 (2023)
ABSTRACTDepending on the viewpoint of the author, discourse is presented in narration, or rather, discourse is first formed in the perception, narration, and interpretation of the history of civilizations. However, Western scholars have dominated the
Externí odkaz:
https://doaj.org/article/7be4660a331e4011b9e44492c5b5f835
Autor:
Zhuang Peina, Liu Shishi
Publikováno v:
Comparative Literature: East & West, Vol 7, Iss 2, Pp 188-200 (2023)
ABSTRACTRecent studies on the relation between the body and nature have become increasingly prominent due to the environmental issues confronting the whole of mankind. This paper, based on the comparative cultural analysis of the two concepts, argues
Externí odkaz:
https://doaj.org/article/16417f2dee53479a9d6bf61bafd7bba7
Autor:
Zhong, Zhaohui, Fan, Tingting, He, Yao, Liu, Shishi, Zheng, Xuelian, Xu, Yang, Ren, Jingqi, Yuan, Hua, Xu, Zhengyan, Zhang, Yong
Publikováno v:
In Plant Communications 9 September 2024 5(9)
Functional binary datasets occur frequently in real practice, whereas discrete characteristics of the data can bring challenges to model estimation. In this paper, we propose a sparse logistic functional principal component analysis (SLFPCA) method t
Externí odkaz:
http://arxiv.org/abs/2109.08009
Autor:
Yang, Yuqing, Xie, Yicheng, Ling, Yue, Dong, Zexin, Li, Peishan, Liu, Shishi, Li, Shuti, Wu, Shuanghong, Wang, Xingfu
Publikováno v:
In Nano Energy April 2024 122
This paper is concerned with model averaging estimation for partially linear functional score models. These models predict a scalar response using both parametric effect of scalar predictors and non-parametric effect of a functional predictor. Within
Externí odkaz:
http://arxiv.org/abs/2105.00953
Autor:
Liu, Shishi, Zhang, Jingxiao
In this paper, we propose a model averaging approach for addressing model uncertainty in the context of partial linear functional additive models. These models are designed to describe the relation between a response and mixed-types of predictors by
Externí odkaz:
http://arxiv.org/abs/2105.00966
Functional principal component analysis is essential in functional data analysis, but the inferences will become unconvincing when some non-Gaussian characteristics occur, such as heavy tail and skewness. The focus of this paper is to develop a robus
Externí odkaz:
http://arxiv.org/abs/2102.00911
Functional principal component analysis (FPCA) could become invalid when data involve non-Gaussian features. Therefore, we aim to develop a general FPCA method to adapt to such non-Gaussian cases. A Kenall's $\tau$ function, which possesses identical
Externí odkaz:
http://arxiv.org/abs/2102.01286
Autor:
Sun, Miaolan, Xie, Yuxiang, Zhong, Cong, Huang, Yixin, Chen, Hui, Huang, Huayu, Dai, Peng, Liu, Shishi, Zheng, Weichen, Liu, Chengyong, Liao, Shangju, Huang, Ling, Sun, Shigang, Wang, Xuefeng
Publikováno v:
In Energy Storage Materials February 2024 65