Course Topics Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous ...

The methods and results reflect the deep connection between the functional linear regression model and the Gaussian sequence model. We also present an extensive simulation study and a real data ...

For example, in the third graph, if you have a line similar to the green one, you should consider using logarithms in order to make it linear! There are lots of things to do so testing all of them ...

Original Article Published: 12 March 2014 Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits T Qi, B Jiang, Z Zhu, C Wei, Y Gao, S Zhu, H Xu & X Lou ...

The measure is in the same spirit as Achen's (1982) "level importance" measure for linear models and thus fills an important gap in logit regression analysis. We show, on the basis of simulations and ...

Diet models based on goal programming (GP) are valuable tools in designing diets that comply with nutritional, palatability and cost constraints. Results derived from GP models are usually very ...