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We compared several penalties, including the elastic net, ridge, Lasso, MCP and the normal-exponential-γ shrinkage prior implemented in the hyperlasso software, to standard single locus analysis and simple forward stepwise regression.
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The model of evolution used to infer divergence time estimates was based on the priors implemented in the MrBayes inference across the locus partitions: GTR+I+Γ, four gamma categories, and empirical base frequencies.
These include nonconvex bridge regression (L q penalty for 0< q<1), the NEG prior implemented in hyperlasso [Hoggart et al., 2008] and thresholding penalties such as the smoothly clipped absolute deviation penalty (SCAD) [Fan and Li, 2001] and the MCP [Breheny and Huang, 2008; Zhang, 2007].
To incorporate spatial information, we used a Bayesian clustering method with a spatially explicit prior implemented in TESS 2.1 (Chen et al. 2007).
Sparsely sampled outgroups violate the basic assumption of most (if not all) the tree priors implemented in Bayesian dating, namely that the taxon sampling is random and consistent across all clades in the tree (see p. 98 of Drummond and Bouckaert [ 105]).
The priors used during the normalization-segmentation step were a symmetrical version of the default priors implemented in SPM5.
We also considered additional priors as implemented in the new segmentation toolbox of SPM8, which have been optimised for segmenting high resolution anatomical images (e.g. T1-weighted) of normal brains.
The first such prior model is implemented in the regularization parameter and enables the detection of discontinuities in the DRT.
Both of these adapted interventions were reviewed by an expert panel and a community advisory board in Cape Town prior to being implemented in the field.
The PAQ used in our study was designed using data from the Newcastle 85+ pilot study and then trialled in this age group prior to being implemented in the main study.
BGS-NMF algorithms with Laplacian prior and LSM prior shall be both implemented in the experiments.
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