Results 31 to 40 of about 371,316 (301)
Modeling Crude Oil Price Dynamics: Investigation of Jump and Volatility Using Stochastic Volatility Models (Case study: WTI crude oil prices in 2020 and 2021) [PDF]
Pizhūhishnāmah-i Iqtiṣād-i Inirzhī-i Īrān, 2020 Due to the strategic role of volatility and instability of crude oil prices and their effects on all countries of the world, different methods of modeling and forecasting are necessary.
mojtaba rostami +1 more
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Approximate Bayesian Inference Based on Expected Evaluations [PDF]
, 2023 Approximate Bayesian computing (ABC) and Bayesian Synthetic likelihood (BSL) are two popular families of methods to evaluate the posterior distribution when the likelihood function is not available or tractable.
Hammer, Hugo Lewi, Riegler, Michael
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Entropy, 2018 The 37th edition of MaxEnt was held in Brazil, hosting several distinguished researchers and students. The workshop offered four tutorials, nine invited talks, twenty four oral presentations and twenty seven poster presentations. All submissions received
Teresa C. M. Dias +3 more
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Approximate Bayesian inference for doubly robust estimation [PDF]
, 2015 Doubly robust estimators are typically constructed by combining outcome regression and propensity score models to satisfy moment restrictions that ensure consistent estimation of causal quantities provided at least one of the component models is ...
McCoy, EJ, Graham, DJ, Stephens, DA
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Bayesian quantification of thermodynamic uncertainties in dense gas flows [PDF]
, 2014 A Bayesian inference methodology is developed for calibrating complex equations of state used in numerical fluid flow solvers. Precisely, the input parameters of three equations of state commonly used for modeling the thermodynamic behavior of so-called ...
CINNELLA, Paola, X. Merle, MERLE, Xavier
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Optimization of non-periodic inspection of structural components by Bayesian approach
Mechanical Engineering Journal, 2018 This paper presents an advanced Bayesian analysis method to determine the appropriate non-periodic inspection intervals of fatigue-sensitive structures. The calculation procedure of the posterior distribution is improved compared to the previous methods.
Haoyu HUANG +3 more
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Сравнительная политикаThis article endeavors to construct a composite indicator designed to facilitate the comparative assessment of institutional capacities across diverse political systems.
I. Ye. Gorelskiy
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, 2003 Bayesian methods allow for a simple and intuitive representation of the function spaces used by kernel methods. This chapter describes the basic principles of Gaussian Processes, their implementation and their connection to other kernel-based Bayesian estimation methods, such as the Relevance Vector Machine.
Alexander J. Smola, Bernhard Schölkopf
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Power prior elicitation in Bayesian quantile regression [PDF]
, 2011 This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2011 Rahim Alhamzawi and Keming Yu.We address a quantile dependent prior for Bayesian quantile regression.
Rahim Alhamzawi +3 more
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Bayesian inference: more than Bayes’s theorem
Frontiers in Astronomy and Space SciencesBayesian inference gets its name from Bayes’s theorem, expressing posterior probabilities for hypotheses about a data generating process as the (normalized) product of prior probabilities and a likelihood function.
Thomas J. Loredo, Robert L. Wolpert
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