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The performance of statistical methods for modeling resource selection by animals is difficult to evaluate with field data because true selection patterns are unknown.
Often, the performance of statistical methods can be improved by combining them with linguistic analysis techniques [24 27].
Simulation studies are routinely used to assess the performance of statistical methods.
In the current study, we investigated the performance of statistical methods for DTC, AITC, frequentist and Bayesian MTC.
Data normalization has substantial impact on the performance of statistical methods for DE analysis of sequence count data.
Empirical studies seeking to verify the performance of statistical methods frequently lack the capabilities of simulation-based analysis, where the accuracy of parametric estimation can be measured.
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Time-related issues can be of concern, especially for simulation studies, where a large number of replications needed to be analyzed to assess the performances of statistical methods.
KBC participated in the formulation of the study, choice of statistical methods, and performance of statistical analyses.
We propose that the evaluation of the building performance should be based on thorough application of statistical methods.
Furthermore, we made use of statistical methods to improve the performances of systems by successfully dealing with the textureless objects.
Statistical Papers provides a forum for the presentation and critical assessment of statistical methods.
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performance of statistical analyses
performance of such methods
performance of statistical features
performance of statistical data
performance of statistical tests
performance of statistical strategies
performance of statistical parameters
performance of other methods
performance of sparse methods
performance of different methods
performance of statistical techniques
performance of parametric methods
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