The course covers linear and polynomial regression, logistic regression, and linear discriminant analysis; cross-validation and bootstrapping, model selection and regularisation methods (ridge and ...

For the model ... regression coefficients. Instead, we present graphs of the fitted curves, along with partial adjusted R square (“variance explained”) contributed by the expected time to diagnosis ...

Besides normality, these traditional regression models assumed linearity, independence and homogeneity of variance of the errors. Heterogeneous data, skewed data or data, where the response ...

But it does – and the Tesla Model 3 is the best known. It is, famously, a fully electric car – Tesla doesn’t do petrols, diesels or even hybrids – and it’s the US brand’s smallest and ...

Abstract: This article explores the problem of prescribed-time stabilization for a class of high-order polynomial nonlinear systems with unknown time-varying nonlinearities. The key technique behind ...

Moreover, in this work, it is combined with nonlinear model predictive control (NMPC) to perform maneuver control. Simulation studies show that EISINDYc-NMPC has improved prediction accuracy, control ...

Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European ...