Evans and Rosenthal consider ways to sample from a distribution with density given by:f(y) = c e^(-y^4)(1+|y|)^3where c is a normalizing constant and y is defined on the whole real line.Use of the probability integral transform (section 1.10.8) is not feasible in this setting, given the complexity of inverting the cumulative density function.The Metropolis–Hastings algorithm is a Markov Chain

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**Tags:** Bayesian methods, MCMC, Metropolis-Hastings algorithm, pathological distribution, rejection sampling