Výsledky vyhledávání - "expectation/conditional maximization algorithm"

A practical model‐based segmentation approach for improved activation detection in single‐subject functional magnetic resonance imaging studies Autor Chen, Wei‐Chen, Maitra, Ranjan

“…‐signal contexts and single‐subject studies. Accurate activation detection can be guided by the fact that very few voxels are, in reality, truly activated…”
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Lifetime prognostics for deteriorating systems with time-varying random jumps Autor Zhang, Jian-Xun, Hu, Chang-Hua, He, Xiao, Si, Xiao-Sheng, Liu, Yang, Zhou, Dong-Hua

“…•A degradation model with time-varying random jumps is presented.•The approximated analytical lifetime of the proposed model is derived.•A two-step parameters…”
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Multivariate t nonlinear mixed-effects models for multi-outcome longitudinal data with missing values Autor Wang, Wan-Lun, Lin, Tsung-I

“…‐subject errors are assumed to be normally distributed for mathematical tractability and computational simplicity…”
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Estimation in multivariate t$t$ linear mixed models for longitudinal data with multiple outputs: Application to PBCseq data analysis Autor Taavoni, Mozhgan, Arashi, Mohammad

“…In many biomedical studies or clinical trials, we have data with more than one response variable on the same subject repeatedly measured over time…”
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Multivariate generalized hyperbolic laws for modeling financial log‐returns: Empirical and theoretical considerations Autor Fotopoulos, Stergios B., Paparas, Alex, Jandhyala, Venkata K.

“…Summary The aim of this study is to consider the multivariate generalized hyperbolic (MGH) distribution for modeling financial log‐returns. Beginning with the…”
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A robust threshold t linear mixed model for subgroup identification using multivariate T distributions Autor Zhang, Rui, Qin, Guoyou, Tu, Dongsheng

“… In this paper, we propose a robust subgroup identification method for longitudinal data by developing a robust threshold t linear mixed-effects model, where random effects and within-subject errors…”
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Mixture of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values Autor Wang, Wan-Lun

“… Under a missing at random mechanism, a pseudo-data version of the alternating expectation-conditional maximization algorithm is developed to carry out maximum likelihood estimation and impute missing…”
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Estimation in multivariate linear mixed models for longitudinal data with multiple outputs: Application to PBCseq data analysis Autor Taavoni, Mozhgan, Arashi, Mohammad

“…In many biomedical studies or clinical trials, we have data with more than one response variable on the same subject repeatedly measured over time…”
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