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Sentence examples for based on penalized likelihood from inspiring English sources

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Divergence time estimates based on penalized likelihood of Rag1 show a most recent common ancestor of modern Amphiuma (i.e., the split between A. tridactylum and A. means+A. pholeter) to be 5.0±1.5 MYA or 7.8±2.3 MYA, and divergence between A. means and A. pholeter to be 2.1±0.8 MYA or 3.2±1.2 MYA.

The alternative algorithm based on penalized likelihood revealed highly congruent results with those obtained by the Bayesian approach (Table 1).

Estimation methods for DLNMs not requiring the completely parametric approach proposed here seems attractive and possible, in particular based on penalized likelihood [ 24] or Bayesian methods [ 25].

IsoLasso is based on penalized likelihood maximization like FlipFlop and NSMAP, but starts from a restricted set of isoforms the same set returned by Cufflinks for single-end data.

A recent phylogenetic study based on penalized likelihood analysis [ 72] indicated that Medicago, Lotus and Cicer are closer and fall in the same galegoid clade, however, the divergence/difference in the pattern of ESTs may be attributed to the fact that gene expression is shaped by cellular environment besides ecological niche of the corresponding organism.

Similar(55)

If one considers selection based on penalized error measures, the level of penalty required to exclude the covariate is indicative of the explanatory power.

Model selection was based on penalized estimation of a linear model by using the lasso (l1) penalty [ 16, 17].

Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called "large P and small N" problem.

This rescaling was performed using a semiparametric method based on the penalized likelihood method of Sanderson (2002) as implemented in the chronopl function within the ape R package (Paradis et al. 2004).

He has divided the e-tailers into three tiers, based on their likelihood for success.

This technique builds a statistical model based on maximum likelihood.

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