The SigShrink function applies a penalized shrinkage to data with small amplitudes.
We embed the auxiliary importance sampler in a penalized maximum likelihood framework which produces more accurate and computationally efficient parameter estimates.
Optimization of the l p is achieved by a Newton method which shares several features with a penalized iteratively re-weighted least squares scheme standard for GLM estimation.
Accordingly, we perform parameter estimation using a penalized partial likelihood criterion [17] that forces the solution to the estimation problem to have small L2-norm.
The information criterion includes a penalized function based on number of estimated parameters.
The time trend in the hazard of infection is specified by a penalized B-spline.
We fit the differential equation model to published microarray data using a penalized nonlinear least squares approach.
We later continued testing all possible QTL combinations and then choosing the one that maximizes a penalized log-likelihood.
Using a penalized regression model (ridge regression of Hoerl and Kennard 1970a, b) can be a solution to this problem.
The smoothed indices, and, are calculated using a spline smoothing or local fit technique, such as a penalized regression [ 37].
