Results 21 to 30 of about 168,901 (276)
MCMC‐driven importance samplers
Monte Carlo sampling methods are the standard procedure for approximating complicated integrals of multidimensional posterior distributions in Bayesian inference. In this work, we focus on the class of Layered Adaptive Importance Sampling (LAIS) scheme, which is a family of adaptive importance samplers where Markov chain Monte Carlo algorithms are ...
F. Llorente +4 more
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Locking phenomena in finite element analysis of deep beam and removal method
Since earlier 30 years ago, Finite Element Methods (FEM) has become an indispensable tool of engineers for analysis mechanical behaviour of structures. Generally displacement models are used in most usual problems.
Nguyen Thang Hoa, Tran Ich Thinh
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Kali Kupang plays an important role in the life of the people of Pekalongan and its surrounding areas. However, until recently, not many hydrological studies have been carried out in this area.
Sandy H. S. Herho
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Subsampling MCMC - An introduction for the survey statistician [PDF]
The rapid development of computing power and efficient Markov Chain Monte Carlo (MCMC) simulation algorithms have revolutionized Bayesian statistics, making it a highly practical inference method in applied work.
Dang, Khue-Dung +4 more
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bamdit: An R Package for Bayesian Meta-Analysis of Diagnostic Test Data
In this paper we present the R package bamdit. The name of the package stands for "Bayesian meta-analysis of diagnostic test data". bamdit was developed with the aim of simplifying the use of models in meta-analysis, that up to now have demanded great ...
Pablo Emilio Verde
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Cervical cancer is the most common cancer that causes death in women. This cancer is mainly caused by Human Papilloma Virus (HPV). It is estimated that 52 million of Indonesian women are at risk of having cancer, and 36% of female cancer patients suffer ...
Nur Mahmudah, Fetrika Anggraini
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An improved method of groundwater model structural uncertainty analysis
Gaussian Process Regression (GPR) is a supervised learning algorithm based on Bayesian theory, which is widely used in model structural uncertainty analysis based on data-driven method (DDM).
Xiaozhuo SUN +3 more
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Aquifer hydraulic conductivity prediction via coupling model of MCMC-ANN
Grain-size distribution data, as a substitute for measuring hydraulic conductivity (K), has often been used to get K value indirectly. With grain-size distribution data of 150 sets of samples being input data, this study combined the Artificial Neural ...
Chun-lei GUI +3 more
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Evaluating the Usability of a Medical Care Monitoring Center System Using Heuristic Method [PDF]
Introduction: Simultaneously with the COVID-19 epidemic, many efforts were made to manage and treat the disease. One of the main activities was the development of health information systems to help monitor this disease, but due to the speed of the ...
Zohreh Hashemi +3 more
doaj
Renal Organic Cation Transporter 2 (OCT2) plays a major role in metformin elimination. Daclatasvir, a Direct-Acting Antiviral (DAA), is an OCT2 inhibitor.
Mohamed Raslan +2 more
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