Zobrazeno 1 - 10
of 325
pro vyhledávání: '"Fu, Liya"'
Autor:
Han, Haohui, Fu, Liya
Big data is ubiquitous in practices, and it has also led to heavy computation burden. To reduce the calculation cost and ensure the effectiveness of parameter estimators, an optimal subset sampling method is proposed to estimate the parameters in mar
Externí odkaz:
http://arxiv.org/abs/2311.08812
Publikováno v:
In Water Research 1 September 2024 261
Autor:
Farjand, Arya, Fu, Liya, Rummy, Paul, Halaçlar, Kazim, Wang, Jian, You, Qiong, Su, Hui, Bi, Shundong
Publikováno v:
In Heliyon 15 May 2024 10(9)
Publikováno v:
In Chemosphere February 2024 349
As an effective nonparametric method, empirical likelihood (EL) is appealing in combining estimating equations flexibly and adaptively for incorporating data information. To select important variables and estimating equations in the sparse high-dimen
Externí odkaz:
http://arxiv.org/abs/2103.10613
Publikováno v:
Statistics in Medicine.(2021) 1-20
This paper proposes a new robust smooth-threshold estimating equation to select important variables and automatically estimate parameters for high dimensional longitudinal data. A novel working correlation matrix is proposed to capture correlations w
Externí odkaz:
http://arxiv.org/abs/2011.06241
Autor:
Fu, Liya, Wang, Panxin, Wu, Changyong, Zhou, Yuexi, Song, Yudong, Guo, Shujun, Li, Zhimin, Zhou, Jian
Publikováno v:
In Journal of Environmental Management 1 January 2024 349
Publikováno v:
In Journal of Statistical Planning and Inference January 2024 228:11-22
Publikováno v:
In Separation and Purification Technology 19 February 2025 354 Part 1
In medical studies, the collected covariates usually contain underlying outliers. For clustered /longitudinal data with censored observations, the traditional Gehan-type estimator is robust to outliers existing in response but sensitive to outliers i
Externí odkaz:
http://arxiv.org/abs/2003.03948