Exact(1)
Using the notion behind the DBC, we combine the robust discrepancy measure between a nested model M α and the full model with the measure of complexity of the model M α to define a robust model selection criterion in GLM.
Similar(59)
The robust measure of discrepancy between a nested model M α and the full model (Cantoni and Ronchetti 2001) is Lambda_{QM} = D_{QM} left( {varvec{y},widehat{varvec{mu}}_{varvec{alpha}} } right) - D_{QM} left( {varvec{y},widehat{varvec{mu}}} right), (13 where, (widehat{varvec{mu}}_{varvec{alpha}}) and (widehat{varvec{mu}}) are robust estimators of μ α and μ respectively.
The second of these assumptions is clearly violated with the data from Maryland; however the results appear to be reasonably robust to this discrepancy, except in the case of Cumberland.
Along with the low discrepancy rate, robust QC at variable sites, and lack of detectable strand bias, the absence of detectable numts provided confidence in the estimates of diversity obtained from our sperm whale mitogenome alignments.
On the other hand, the two-step sequential method based on group sparsity is robust against such phase discrepancies because the performance of the group sparsity-based method does not directly depend on the coherent combination of the multiple Doppler signatures.
Even though these detectors do not ensure the constant false alarm rate (CFAR) property with respect to the covariance matrix of the disturbance, a sensitivity analysis has shown that the threshold setting is very robust with respect to possible discrepancies between the design and the operating conditions.
The PG model, by virtue of its constituent gamma distribution, represents some degree of averaging and it should be sufficiently robust to account for minor discrepancies.
37 We will implement robust quality assurance processes to limit discrepancies between data collectors by training, measuring inter-rater reliabilities and having regular review meetings (see component 7).
The findings do provide evidence of robust and large effects for the current ideal discrepancy as measured by figural rating scales, but argue against including multiple questions about ideal body preferences on these types of scales.
Furthermore, a discrepancy was observed between the robust immunostaining of D1/D5 receptors in the hippocampus and nearly-absent dopaminergic fibers (Smith and Greene 2012).
As the information recorded for an individual may vary from dataset to dataset - due to either differences in reporting (e.g. in first name) or errors - a robust linkage process should allow for some discrepancy in reported characteristics.
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