Then we plucked the top 20 by applying a weighted formula based on comparable metrics.
Then, by applying a weighted normalization routine to these consecutive values, an implicit stabilizer is formed: (19).
Therefore, the demographic distribution from this sample of 10,030 respondents was adjusted to match the 2009 CPS for age and sex (15) by applying a weighted adjustment to each respondent and their answers.
Subsequently, the ten thousand best parameter sets (lowest X d values) were selected and optimized to describe the experimental data, by applying a weighted non-linear least squares algorithm that minimizes X d : (4) θ ^ = arg min θ X d where θ ^ represents the optimized parameter set.
Subsequently, the background-subtracted fluorescent intensity in each wavelength (channel 1 for indodicarbocyanine [Cy5] and channel 2 for indocarbocyanine [Cy3]) was normalized using the MIDAS software (available from TIGR, ) [ 61] and by applying a locally weighted linear regression (Lowess), as previously described [ 24].
The acceptable parameter sets from phenotype A could be used as initial values and reoptimized by once more applying a weighted non-linear least squares algorithm, minimizing X d with respect to the experimental data of phenotype B. Subsequently, necessary parameter adaptations can be identified which are responsible for the change of phenotype.
The tumors were positioned in the isocenter of the magnet and were imaged axially in a single section through the tumor center by applying a diffusion-weighted single-shot fast spin echo sequence with ETL = 84 and TR = 5002 ms.
DW-MRI was carried out by applying a diffusion-weighted single-shot fast spin echo pulse sequence (RARE) with a TR of 1300 ms, a TE of 26 ms, an image matrix of 64 × 64, a FOV of 3 × 3 cm, a slice thickness of 0.7 mm, and a slice gap of 0.3 mm.
Scanned array images were quantified and normalized by applying a LOWESS (locally weighted scatterplot smoothing) algorithm to the data within print-tip groups using the TM4 software package [ 31].
To assess for possible publication bias, we used the test proposed by Egger and colleagues [ 16], which provides an assessment of funnel-plot asymmetry (expressed as a P value) by applying an inverse-variance weighted approach.
A solution could also be reached in a L1-norm sense by applying an iteratively re-weighted least-squares algorithm with Huber weights in order to obtain a robust solution by iteratively weighting the effect of outlier data in the parameter estimation.
