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This paper considers integral approximation via importance sampling where the importance sampler is chosen from a family of skew-Student distributions. This is an alternative class of distributions than is typically considered in importance sampling applications. We describe variate generation and propose adaptive methods for fitting a member of the skew-Student family to a particular integral. We also demonstrate the utility of the approach in several examples.

Moment matching adaptive importance sampling with skew-student proposals