33 citations · 50 across the 9 of their papers we have counts for
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General Effect Modelling (GEM) -- Part 3. GEM applied on proteome data of cerebrospinal fluid of multiple sclerosis and clinically isolated syndrome
Ellen Færgestad Mosleth, Kjell-Morten Myhr, Christian Alexander Vedeler +4
The novel data analytical platform General Effect Modelling (GEM), is an umbrella platform covering different data analytical methods that handle data with multiple design variable…
General Effect Modelling (GEM) -- Part 2. Multivariate GEM applied to gene expression data of type 2 diabetes detects information that is lost by univariate validation
Ellen Færgestad Mosleth, Simon Erling Nitter Dankel, Gunnar Mellgren +7
General Effect Modelling (GEM) is an umbrella over different methods that utilise effects in the analyses of data with multiple design variables and multivariate responses. To demo…
General Effect Modelling (GEM) -- Part 1. Method description
Ellen Færgestad Mosleth, Kristian Hovde Liland
We present a flexible tool, called General Effect Modelling (GEM), for the analysis of any multivariate data influenced by one or more qualitative (categorical) or quantitative (co…
A New Formula for Faster Computation of the K-Fold Cross-Validation and Good Regularisation Parameter Values in Ridge Regression
Kristian Hovde Liland, Joakim Skogholt, Ulf Geir Indahl
In the present paper, we prove a new theorem, resulting in an update formula for linear regression model residuals calculating the exact k-fold cross-validation residuals for any c…