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Given that carotenoid traits are likely largely explained by a small number of moderate- to large-effect loci (Wong et al. 2004; Chander et al. 2008; Kandianis et al. 2013), we hypothesized that a variable selection method that shrinks the variance explained by noncontributing markers to near or equal to zero, such as LASSO or elastic net analysis, would show higher predictive ability.
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In contrast to existing methods that shrink the signal samples to zero, SI-LMS and SI-RLS shrink to zero the links that have poor performance or high MSE values.
Unlike existing methods that shrink the signal samples to zero, the proposed SI-LMS and SI-RLS algorithms shrink to zero the links that have poor performance or high MSE values.
One explanation for the observed trend in Figure 1a is that regularization methods that shrink the network weights toward zero are too selective and often identify only a few relevant networks.
We address this practical problem with a method that makes use of osmosis to shrink large droplets to a size suitable for FACS sorting.
The results show that the heat-shrink approach is a simple fabrication method that may be advantageous in large-area, low power density applications.
Here we report the first application of a new method of EEG analysis to schizophrenia research a method that determines EEG synchronization by relating it to the shrinking of the state-space embedding dimension.
When testing for differential expression, the QuasiSeq package employs a quasi-likelihood method that incorporates uncertainty in the estimated variances and provides a self-tuning approach to shrinking gene-specific dispersion estimates [ 59].
This method adapts an iterative algorithm proposed by Wipf and Nagarajan (2008) that uses an adaptive lasso algorithm that shrinks the diagonal entries towards zero.
That shrinks the supply of shortable stock.
European sales fell 1.5 percent in a market that shrank 6.8 percent.
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