Stochastic gradient descent (SGD) provides a scalable way to compute parameter estimates in applications involving large-scale data or streaming data. As an alternative version, averaged implicit SGD ...

Divergence estimators have emerged as quintessential tools in statistical inference, particularly in contexts where traditional likelihood‐based methods fail under model misspecification or data ...

Estimating non-linear functions of multinomial probabilities is a common problem in epidemiology. Maximum likelihood estimates of non-linear functions are easily obtained. However, only asymptotic ...