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[Various random number generators are proposed to obtain random variates following the univariate normal distribution. Box and Muller (1958) is a pioneering work on such a random number generator; see, e.g., Devroye (1986) for others. However, in many Bayesian analyses, multivariate normal random variates subject to linear constraints are often needed to conduct statistical inference. The discrete/continuous choice models under increasing block rate pricing in previous chapters are an example because their sampling algorithms include a step to draw such random variates (a step for elasticity parameters). In this chapter, we focus on simulators for multivariate normal variates subject to linear constraints.]
Published: Dec 17, 2019
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