Introducing Monte Carlo Methods with R

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Bidirectional Helmholtz Machines (2015, methodology): “Importance sampling efficiency A widely used metric to estimate the quality of an importance sampling estimator is the effective sampling size (ESS), given by êss = ( ∑K k=1 ωk) 2/( ∑K k=1 ω 2 k) (see, e.g., Robert & Casella (2009)).”
Jelly Bean World: A Testbed for Never-Ending Learning (2020, methodology): “The second step is performed by using Metropolis-Hastings (MH) (Robert & Casella, 2010) to sample the items that the new patch contains, from the distribution deﬁned in Equation 1.”
Bayesian interpolation of unequally spaced time series (2015, unknown): “In both cases, the acceptance rates are adequate according to (Robert and Casella 2010, ch.6).”
A physiological analogy of the niche for projecting the potential distribution of plants (2012, unknown): “Importance sampling is a stochastic method for generating samples from a target distribution; these samples can be used to estimate properties (mean, quantiles) of the target distribution (Robert & Casella, 2009).”