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An independent line of evidence, based on model selection, also indicated that intensity-based models are preferred over ratio-based models for the analysis of dual-color microarray data.
Additionally and independently for each transcript, a class variable for family and covariates for pre- and post-globin-reduction RIN, and 5′-3′ treadcript read skewness were considered to be included based on model selection using Aikake information criterion (AIC) comparisons to select the best model.
We present an approach, based on model selection criteria —such as Akaike information criterion (AIC), Bayesian information criterion (BIC) and deviance information criterion (DIC)— to select the most appropriate model, among a set of four candidate models —linear, power, exponential and logistic—, to estimate the deformation modulus of a rock mass, given a set of observed data.
The technique is based on model selection by cross-validation and produces models that allow computation of an information score for any signal-length sequence.
Tables 3, 4 and 5 also display the performance obtained with the methods described in Section 4.2 based on model selection.
This paper presents a Bayesian method for burst identification based on model selection and demonstrates the detection of bursts consisting of 10% signal amplitude.
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Based on model-selection tests conducted with jModelTest (v2.1.4; Darriba et al. 2012) to determine the most likely model of molecular evolution, we used the general time-reversible model with a gamma shape parameter (GTR + G) and four site categories.
In order to minimize the effect of false-positive interactions, we applied AIC in the last step of network construction to eliminate the false-positive interactions based on model order selection.
The statistical analyses are based on model optimisation and selection and are used to evaluate the shape of vertical amplitude ratio profiles.
The generic FRM achieved results that were comparable to those obtained with more traditional approaches based on model and variable selections.
TABLUP and GBLUP have some features that other genomic selection methods based on model (1) lack.
More suggestions(15)
based on path selection
based on model calibration
based on model reference
based on relay selection
based on attractor selection
based on feature selection
based on model chain
based on model test
based on model checking
based on model procedure
based on tournament selection
based on sequence selection
based on model transformation
based on model reduction
based on model identification
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