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Acquire a robust understanding of logit model parameters beyond the canonical odds ratio interpretationAll Images By AuthorLogistic regressions, also referred to as a logit models, are powerful alternatives to linear regressions that allow one to model a dichotomous, binary outcome (i.e., 0 or 1) and provide notably accurate predictions on the probability of said outcome occurring given an observation. The parameter estimates within logit models can provide insights into how different explanatory variables, or features,…

Recent megafires in Australia and British Columbia have injected unprecedented amounts of smoke into the stratosphere. Modeling led by Los Alamos National Laboratory will help predict the effects of similar future events. Credit: David Peterson, FIREX-AQ New research modeling smoke from two recent megafires sets the stage for better forecasting of how emissions from these global-scale events will behave and impact…