Bayesian approach for probabilistic characterization of sand friction angles

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Bayesian identification of random field model using indirect test data (2016, methodology): “To avoid the computational complexity in solving the posterior distribution that is considered as one key limitation of Bayesian methods in literature (e.g., Zhang et al., 2009; Wang et al., 2010), the next subsection uses MCMCS to generate a large number of X samples to describe the posterior distr”
Impact of sample size on geotechnical probabilistic model identification (2017, methodology): “The sample size of geotechnical data in a specific site is typically less than 30 for common geotechnical parameters [27,31,32,7].”
Statistical characterization of random field parameters using frequentist and Bayesian approaches (2016, methodology): “2014), the fluctuation function method (Wickremesinghe and Campanella 1993; Cafaro and Cherubini 2002), the maximum likelihood (ML) method (DeGroot and Baecher 1993), and the Bayesian method (Wang et al. 2010).”