Sentence examples for ridge model from inspiring English sources

The general linear model (PROC GLM) was used to assess the ridge model.

SWs were simulated in an idealised 3D ridge model as shown in Figure 7.

This is demonstrated in the results of ridge regression (ridge.add) on the pre-CC: In this context, with only moderate uncertainty for most individuals at most loci, the performance of a simple ROP-based eight-allele ridge model (which we consider an optimistic equivalent to an unpenalized regression of the same model) approaches that of the best Diploffect-based method.

The Ridge model results were also compared to results from the Lasso model to hone the final model.

When considering all cases and all controls, we identified a panel of five CpG sites (Model I: IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, TAL1_P817) that were the first five CpGs to enter and remain in the Lasso model and also the five largest coefficients from the Ridge model.

The weights <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0017845.e016.PNG" class= inline-graphic"/> for individual genes in the jth gene set were the corresponding estimated coefficients from the training set using the Cox-ridge model (1) (Figure 1A).

In this paper to adapt indefinite kernels to ridge regression model, an indefinite kernel ridge regression model is proposed.

Some of the data used to propose the (dormant) ridge subduction model was not available at the time Seton et al. (2012)) performed their analysis of paleoplate geometry.

In combination with previous studies in the Chinese Altai, we suggest a two-sided ridge subduction model for the Junggar-Altai region.

Note that equation (5) is essentially similar to the ridge regression model.

Furthermore, we applied the ridge regression model to estimate optimal regression coefficients for 88 genes of the PFS-related profile (Table 2), and calculated the prognostic index for each sample using equation (1) as reported previously [18].