Genetic algorithms (GAs) are increasingly used in large and complex optimisation problems. Here we use GAs to optimise fitness functions related to ridge regression, which is a classical statistical procedure for dealing with a large number of features in a multivariable, linear regression setting. The algorithm avoids overfitting, gracefully handles collinearity and leads to easily interpretab...

The paper discusses penalised spline (P -spline) smoothing for hazard regression of multivariable survival data. Non-proportional hazard functions are fitted in a numerically handy manner by employing Poisson regression which results from numerical integration of the cumulative hazard function. Multivariate smoothing parameters are selected by utilizing the connection between P -spline smoothin...

We discuss some features of the orthogonalization methods commonly applied to QSPR QSAR studies. We outline the well known multivariable linear regression analysis in vector form in order to compare mainly Randic and Gram-Schmidt orthogonalization procedures and also cast the basis for other approaches like Löwdin’s one. We expect that present review may become the starting point for future dev...

Methods This paper reports on the reporting quality of cardiac computed tomography (CCT), single positron emission computed tomography (SPECT), and cardiac magnetic resonance (CMR) diagnostic accuracy studies in randomly selected groups of 50: ‘CMR 1995-2002’, ‘CMR 20042011’, ‘CCT f 1995-2002’, and ‘CCT 2004-2011’, ‘SPECT 1995-2002’, ‘SPECT 2004-2011’. These 300 studies were read against the 25...

The race is not always to the swift nor the battle to the strong — but that’s the way to lay your bets. – Damon Runyon The attempt to predict the values on some dependent variable by a function of independent variables is typically approached by simple or multiple regression, for one and more than one predictor, respectively. The most common combination rule is a linear function of the independ...

1. Residuals from linear regressions are used frequently in statistical analysis, often for the purpose of controlling for unwanted effects in multivariable datasets. This paper criticizes the practice, building upon recent critiques. 2. Regression of residuals is often used as an alternative to multiple regression, often with the aim of controlling for confounding variables. When correlations ...

OBJECTIVE Genetic programming is a search method that can be used to solve complex associations between large numbers of variables. It has been used, for example, for myoelectrical signal recognition, but its value for medical prediction as in diagnostic and prognostic settings, has not been documented. STUDY DESIGN AND SETTING We compared genetic programming and the commonly used logistic re...