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Table 1 Sensitivities, specificities, and accuracies of the quantile and projection quantile methods for the simulated data from duplicated experiments

From: Outlier Detection using Projection Quantile Regression for Mass Spectrometry Data with Low Replication

   Simulated Under
n Method Constant Linear Nonlinear Nonparametric
  Quantile     
  Constant (85.0, 99.5, 98.8) (84.7, 93.1, 92.6) (94.3, 87.6, 87.9) (94.3, 87.7, 88.0)
  Linear (85.0, 99.5, 98.8) (83.7, 99.3, 98.5) (87.7, 94.7, 94.4) (87.3, 94.7, 94.3)
  Nonlinear (85.0, 99.5, 98.8) (83.3, 99.3, 98.5) (87.7, 94.8, 94.5) (86.9, 94.9, 94.5)
  Nonparametric (79.0, 99.2, 98.2) (81.6, 99.1, 98.2) (84.8, 99.0, 98.3) (84.8, 99.0, 98.3)
2 Projection Quantile     
  Constant (88.9, 99.1, 98.6) (69.7, 97.0, 95.7) (78.6, 94.1, 93.4) (78.8, 94.1, 93.3)
  Linear (88.8, 99.1, 98.5) (86.5, 98.9, 98.3) (88.5, 96.1, 95.7) (88.2, 96.1, 95.7)
  Nonlinear (88.8, 99.1, 98.5) (86.5, 98.9, 98.3) (88.3, 98.0, 97.6) (87.9, 98.0, 97.4)
  Nonparametric (83.2, 98.7, 97.9) (84.4, 98.7, 98.0) (86.6, 98.6, 98.0) (86.0, 98.5, 97.9)