In a fuzzy regression discontinuity (RD) design, the probability of treatment jumps when a running variable (R) passes a threshold (R0). Fuzzy RD estimates are obtained via a procedure analogous to ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, ...

Researchers at EPFL have created a mathematical model that helps explain how breaking language into sequences makes modern AI-like chatbots so good at understanding and using words. The work is ...

California Gov. Gavin Newsom (D) spoke to reporters after a federal judge blocked President Donald Trump from deploying the National Guard to Los Angeles. Learn how to build a multivariate linear ...

This page works through an example of fitting a logistic model with the iteratively-reweighted least squares (IRLS) algorithm. If you'd like to examine the algorithm in more detail, here is . (See ...

Often, regression models that appear nonlinear upon first glance are actually linear. The curve estimation procedure can be used to identify the nature of the functional relationships at play in ...

This regression equation, in log transformed form, log10V = clog10A + dlog10DE25, was fit to the data for the 816 lakes. According to Heathcote et al., this log transformation helps to prevent ...

In addition to the regression equation, the report includes odds ratios, confidence limits, likelihood and deviance. As a part of the comprehensive residual analysis, a log regression model can ...

Objective: To establish reference values for the evaluation of respiratory function in healthy children and adults from Mexicali, Baja California, Mexico.Population and Methods: Observational, ...

The least-squares criterion is a method of measuring the accuracy of a line in depicting the data that was used to generate it. That is, the formula determines the line of best fit.