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stat.ME2023★ 1 cited
When Composite Likelihood Meets Stochastic Approximation
Giuseppe Alfonzetti, Ruggero Bellio, Yunxiao Chen +1
A composite likelihood is an inference function derived by multiplying a set of likelihood components. This approach provides a flexible framework for drawing inference when the li…
stat.ME2023★ 2 cited
Consistent and Scalable Composite Likelihood Estimation of Probit Models with Crossed Random Effects
Ruggero Bellio, Swarnadip Ghosh, Art B. Owen +1
Estimation of crossed random effects models commonly requires computational costs that grow faster than linearly in the sample size , often as fast as , making them…