A new study combines drone data, satellite observations, and ground-based flux measurements to examine methane emissions from ...
Background/aims Up-to-date, stratified estimates of the number of individuals affected by glaucoma in the UK are lacking.
Learn to apply Bayes' theorem in financial forecasting for insightful, updated predictions. Enhance decision-making with ...
Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...
These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Abstract: The Bayesian Cramér-Rao bound (CRB) provides a lower bound on the mean square error of any Bayesian estimator under mild regularity conditions. It can be ...
Abstract: Regularized system identification has become a significant complement to more classical system identification. It has been numerically shown that kernel-based regularized estimators often ...
Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
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