A three-step model checking workflow has the potential to revolutionize how researchers evaluate the suitability of their statistical models for specific datasets. Developed by KAUST, the workflow is ...
Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...
Even as data science becomes ubiquitous, we still have a shortage of people who truly understand data. Yaneer Bar-Yam is a Professor and President of the New England Complex Systems Institute. He ...
A number of attempts have been made to forecast the spread and mortality of COVID-19. Two Heritage Foundation analysts examine one common model for doing so. As all epidemiological models are grounded ...
Semiparametric single-index assumptions are widely used dimension reduction approaches that represent a convenient compromise between the parametric and fully nonparametric models for regressions or ...
Examination of the (sample) residuals resulting from the regression analysis can indicate failures of assumptions 1, 3, and 4. Such failures are not necessarily a bad thing: They can point the way to ...
Editors’ Note: Read responses to this essay by epidemiologists Marc Lipsitch and John Ioannidis, as well as a final response by Jonathan Fuller. All these pieces appear in print in Thinking in a ...
Linear mixed models are emerging as the method of choice for association testing in genome-wide association studies (GWAS) because they account for both population stratification and cryptic ...
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