Výsledky vyhledávání

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A novel robust meta-analysis model using the $t$ distribution for outlier accommodation and detection

Autor: Wang, Yue, Zhao, Jianhua, Jiang, Fen, Shi, Lei, Pan, Jianxin

Random effects meta-analysis model is an important tool for integrating results from multiple independent studies. However, the standard model is based on the assumption of normal distributions for both random effects and within-study errors, making

Externí odkaz: http://arxiv.org/abs/2406.04150

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Robust bilinear factor analysis based on the matrix-variate $t$ distribution

Autor: Ma, Xuan, Zhao, Jianhua, Shang, Changchun, Jiang, Fen, Yu, Philip L. H.

Factor Analysis based on multivariate $t$ distribution ($t$fa) is a useful robust tool for extracting common factors on heavy-tailed or contaminated data. However, $t$fa is only applicable to vector data. When $t$fa is applied to matrix data, it is c

Externí odkaz: http://arxiv.org/abs/2401.02203

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Akademický článek

Genetic evidence supporting potential causal roles of EIF4 family in breast cancer: a two-sample randomized Mendelian study

Autor: Jin-Yu Shi, Rui Wen, Jin-Yi Chen, Yi-Qian Feng, Yuan-Yuan Zhang, Si-Jia Hou, Yu-Jia Xi, Jiang-Fen Wang, Ya-Fen Zhang

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)

Abstract Translational control plays a crucial role in the regulation of apoptosis, with the EIF4 family serving as one of the mRNA translation factors that modulate the process of mRNA translation based on mRNA characteristics. To address this poten

Externí odkaz: https://doaj.org/article/97940fd9cbe04ba7a698abeba2955d3c