If program staff suspects you may have used AI tools to complete assignments in ways not explicitly authorized or suspect other violations of the honor code, they will contact you via email. Be sure ...

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

This is a preview. Log in through your library . Abstract Efficiency scores of firms are measured by their distance to an estimated production frontier. The economic literature proposes several ...

Measurement error models address the deviation between observed and true values, thereby refining the reliability of statistical inference. These frameworks are ...

Properties of estimators: unbiasedness, consistency, efficiency and sufficiency. Methods of estimation with particular emphasis given to the method of maximum likelihood. Hypothesis testing and ...

Health researchers need to fully understand the underlying assumptions to uncover cause and effect. Timothy Feeney and Paul Zivich explain Physicians ask, answer, and interpret myriad causal questions ...

• Ahsan, M. N. and Dufour, J-M. (2019). “A simple efficient moment-based estimator for the stochastic volatility model,” Advances in Econometrics. Vol. 40A, pp ...

This online data science specialization is designed to provide you with a solid foundation in probability theory in preparation for the broader study of statistics. The specialization also introduces ...

Networks are often characterized by node heterogeneity for which nodes exhibit different degrees of interaction and link homophily for which nodes sharing common features tend to associate with each ...