Spatio-temporal modelling of extreme low birth rates in U.S. counties by Kai Wang, Yingqing Zhang, Long Bai, Ying Chen, Chengxiu Ling

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Using OCO-2 Observations to Constrain Regional CO₂ Fluxes Estimated with the Vegetation, Photosynthesis and Respiration Model by Igor B. Konovalov, Nikolai A. Golovushkin, Evgeny A. Mareev

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A novel detection method for warhead fragment targets in optical images under dynamic strong interference environments by Guoyi Zhang, Hongxiang Zhang, Zhihua Shen, Deren Kong, Chenhao Ning, Fei Shang, Xiaohu Zhang

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Investigating Feed-Forward Back-Propagation Neural Network with Different Hyperparameters for Inverse Kinematics of a 2-DoF Robotic Manipulator: A Comparative Study by Rania Bouzid, Jyotindra Narayan, Hassène Gritli

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A Roadway Safety Sustainable Approach: Modeling for Real-Time Traffic Crash with Limited Data and Its Reliability Verification by Zhenzhou Yuan, Kun He, Yang Yang

“…Comparatively, the prediction performance of the support vector machine is better than that of Bayesian Logistic. In addition, Bayesian updating method can improve the prediction performance of the transplanted model.…”
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Estimations in a Constant-Stress Partially Accelerated Life Test for Generalized Rayleigh Distribution under Type-II Hybrid Censoring Scheme by Abdalla Rabie, Eslam Hussam, Abdisalam Hassan Muse, Ramy Abdelhamid Aldallal, Amirah Saeed Alharthi, Hassan M. Aljohani

“…Bayesian and E-Bayesian estimates are obtained using Markov chain Monte Carlo (MCMC) methods. …”
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The effect of using Naive Bayes to detect spam email by Sun Zehui

“…This paper focuses on the spam detection method based on the plain Bayesian algorithm. The plain Bayesian algorithm is particularly suitable for spam detection due to its high detection accuracy and its wide application in text classification tasks. …”
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Relationships between Loneliness and Occupational Dysfunction in Community-Dwelling Older Adults: A Cross-Sectional Study by Daiki Nakashima, Keisuke Fujii, Yuta Kubo, Kyosuke Yorozuya

“…The best model was selected by comparing the widely applicable information criterion (WAIC) and the widely applicable Bayesian information criterion (WBIC) for each model. …”
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Testing Data Cloning as the Basis of an Estimator for the Stochastic Volatility in Mean Model by E. Romero, E. Ropero-Moriones

“…This study introduces a Bayesian methodology that leverages data-cloning algorithms to obtain maximum likelihood estimates for SV and SVM model parameters. …”
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Inverse Exponentiated Lomax Power Series Distribution: Model, Estimation, and Application by Amal S. Hassan, Ehab M. Almetwally, Samia C. Gamoura, Ahmed S. M. Metwally

“…The Bayesian estimators of parameters are discussed under squared error and linear exponential loss functions. …”
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Within‐chain parallelization—Giving Stan Jet Fuel for population modeling in pharmacometrics by Casey Davis, Pavan Vaddady

“…To perform a Bayesian data analysis, most models in pharmacometrics require Markov Chain Monte Carlo (MCMC) methods to sample from the posterior distribution. …”
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Economic Development Forecast of China’s General Aviation Industry by Hongqing Liao, Zhigeng Fang, Chuanhui Wang, Xiaqing Liu

“…Aiming at solving the problem of system external impact on China’s general aviation industry, combining functional theory and grey system theory, and applying Bayesian network reasoning technology, a grey Bayesian network reasoning prediction model of system impact and system control is established. …”
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La datation des aqueducs de Lyon : nouvelles données et contribution de l’analyse statistique bayésienne by Christine Oberlin, Jean-Claude Lefèvre

“…In this note, we present the results of the application of Bayesian analysis to the chronology of the Lyon aqueducts.Four aqueducts were built to supply water to the ancient city of Lyon/Lugdunum. …”
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Exploring Influencing Factors of Intercity Mode Choice from View of Entire Travel Chain by Xiaowei Li, Siyu Zhang, Yao Wu, Yuting Wang, Wenbo Wang

“…The results show that the Bayesian mixed multinomial logit model outperforms the traditional Bayesian multinomial logit model, indicating that accommodating the unobserved heterogeneity across observations can improve the model fit. …”
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CPT-Based Probabilistic Characterization of Undrained Shear Strength of Clay by Mi Tian, Xiaotao Sheng

“…This paper presents Bayesian approaches for probabilistic characterization of undrained shear strength using cone penetration test (CPT) data and prior information. …”
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Climate change impact assessment on groundwater level changes: A study of hybrid model techniques by Stephen Afrifa, Tao Zhang, Xin Zhao, Peter Appiahene, Mensah Samuel Yaw

“…A hybrid model (HM) of Bayesian random forest (BRF), Bayesian support vector machine (BSVM), and Bayesian artificial neural network (BANN) is built in this study. …”
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Fuzzy Reliability Analysis of the COVID-19 Mortality Rate Using a New Modified Kies Kumaraswamy Model by Fathy H. Riad, Bader Alruwaili, Ehab M. Almetwally, Eslam Hussam

“…We used both conventional and Bayesian approaches to make various sorts of estimations. …”
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Molecular phylogenetic studies on the lichenicolous Xanthoriicola physciae reveal Antarctic rock-inhabiting fungi and Piedraia species among closest relatives in the Teratosphaeria... by C. Ruibal, A.M. Millanes, D.L. Hawksworth

“…Sequences of the nLSU region were obtained from 11 specimens of X. physciae, which formed a single clade supported both by parsimony (91 %), and maximum likelihood (100 %) bootstraps, and Bayesian Posterior Probabilities (1.0). The closest relatives in the parsimony analysis were species of Piedraria, while in the Bayesian analysis they were those of Friedmanniomyces. …”
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Inferences for Generalized Pareto Distribution Based on Progressive First-Failure Censoring Scheme by Rashad M. El-Sagheer, Taghreed M. Jawa, Neveen Sayed-Ahmed

“…In this article, we consider estimation of the parameters of a generalized Pareto distribution and some lifetime indices such as those relating to reliability and hazard rate functions when the failure data are progressive first-failure censored. Both classical and Bayesian techniques are obtained. In the Bayesian framework, the point estimations of unknown parameters under both symmetric and asymmetric loss functions are discussed, after having been estimated using the conjugate gamma and discrete priors for the shape and scale parameters, respectively. …”
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Some Applications of Bayes' Rule in Probability Theory to Electrocatalytic Reaction Engineering by Thomas Z. Fahidy

“…Bayesian methods stem from the principle of linking prior probability and conditional probability (likelihood) to posterior probability via Bayes' rule. …”
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