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It is well known that in many statistical models, the error of estimators is measured in (L^{p}) norm [10 12].
Due to the complexity of MS/MS spectra, many statistical models have limited accuracy.
Many statistical models exist to model LD, but a model that can detect the structure of haplotypes is missing.
Using this strategy, reliable empirical distributions can be obtained in small sample sizes where many statistical models are prone to inflated type I error and/or FDR.
An M-value is attractive in that it can been used in many statistical models derived for expression arrays that assume normality (Du et al, 2010).
The shrinkage estimator such as the James-Stein estimator has been shown to dominate the least square estimator in many statistical models [ 22, 23].
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Many statistical modelling techniques are being developed, but there remains a need to determine the most appropriate mapping techniques.
Problematically, many statistical modeling techniques utilized in studies of neighborhood effects control for heterogeneity (variance), effectively discounting the complex relationships between environment and health that may be of particular interest (18).
Although many statistical regression models of road traffic relationships have been formulated, they have proven to be unsuitable due to multiple and ill-defined traffic characteristics.
Many statistical translation models can be regarded as weighted logical deduction.
For measuring predictive performance on this noisy data set, we used many statistical classification models.
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