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On the Bayesian multidimensional-matrix polynomial empirical regressionThe problem of the parameters estima-tion for the polynomial in the input variables regression
Diffusion models' calibration by means of Bayesian inference and Euler-Maruyama method. Consequently, their calibration - parameter estimation based on data samples - has attracted considerable
Groundwater-potential mapping using a self-learning bayesian network model: A comparison among metaheuristic algorithms was to determine the optimal network structure of a Bayesian network (BayesNet) machine-learning model using three
Applying Bayesian inference to calibrate local volatility model parameters to the inverse problem, i.e. SDE parameter estimation from discrete-sampled data. This study concerns a problem
Variations in the Duration of the Navigation Period along the Northern Sea Route in the 21st Century Based on Simulations with an Ensemble of Climatic Models: Bayesian Estimates Century Based on Simulations with an Ensemble of Climatic Models: Bayesian Estimates
Максиминная задача оценивания параметров в условиях байесовского точечного засоренияMaximin problem of parameter estimation in conditions of point Bayesian contamination
Total probability and bayes formulae for joint multidimensional–matrix Gaussian distributions multidimensional-matrix Gaussian distributions are given. Using these results, the Bayesian estimations
Оценка вероятностных выводов экспертов в уголовном процессе conclusions into the category of logical
operations performed on the basis of calculations using the Bayesian
On frequency estimation for partially observed system with small noises in state and observation equations the consistency and asymptotic normality of the maximum likelihood and Bayesian estimators in the sense
Current perspectives on the application of bayesian networks in different domainsBayesian networks are powerful tools for representing relations of dependence among variables of a
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