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

This article resulted from our participation in the session on the “role of expert opinion and judgment in statistical inference” at the October 2017 ASA Symposium on Statistical Inference. We present ...

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 course is compulsory on the MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE and Fudan), MSc in Statistics (Financial Statistics) ...

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 ...

Confidence intervals are computed from a random sample and therefore they are also random. The long run behavior of a 95% confidence interval is such that we’d expect 95% of the confidence intervals ...

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

This course is compulsory on the MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (Research), MSc in Statistics (Research), MSc in Statistics ...

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 ...