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Table 2 Sensitivities, specificities, and accuracies of the classical and projection quantile methods for the simulated data from multiple experiments

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

  

Simulated Under

n

Method

Constant

Linear

Nonlinear

Nonparametric

 

Classical

    
 

 Dixon

(10.5, 94.9, 90.7)

(17.3, 94.9, 91.0)

(18.5, 94.9, 91.1)

(17.7, 94.9, 91.0)

 

 Grubbs

(20.8, 89.9, 86.5)

(30.1, 89.9, 87.0)

(34.4, 89.9, 87.2)

(33.7, 90.0, 87.2)

 

Projection Quantile

    

3

 Constant

(90.6, 99.5, 99.0)

(56.0, 98.5, 96.4)

(58.8, 95.7, 93.9)

(57.9, 95.7, 93.8)

 

 Linear

(90.4, 99.5, 99.0)

(84.0, 99.3, 98.5)

(85.1, 96.5, 95.9)

(84.8, 96.6, 96.0)

 

 Nonlinear

(90.4, 99.5, 99.0)

(84.0, 99.3, 98.5)

(84.8, 98.5, 97.8)

(83.5, 98.4, 97.7)

 

 Nonparametric

(85.3, 99.2, 98.5)

(82.0, 99.1, 98.2)

(83.5, 99.0, 98.2)

(83.2, 99.0, 98.2)

 

Classical

    
 

 Dixon

(29.7, 95.0, 91.7)

(44.1, 95.0, 92.4)

(54.9, 94.9, 92.9)

(54.5, 94.9, 92.9)

 

 Grubbs

(49.6, 90.0, 88.0)

(61.1, 90.0, 88.6)

(71.2, 90.0, 89.1)

(70.2, 89.9, 89.0)

 

Projection Quantile

    

4

 Constant

(89.4, 99.6, 99.1)

(46.4, 99.1, 96.5)

(44.3, 97.2, 94.6)

(43.8, 97.3, 94.6)

 

 Linear

(89.3, 99.6, 99.0)

(86.8, 99.5, 98.8)

(86.3, 97.0, 96.5)

(86.4, 97.2, 96.6)

 

 Nonlinear

(89.3, 99.6, 99.0)

(86.8, 99.5, 98.8)

(87.5, 99.2, 98.6)

(87.8, 99.1, 98.5)

 

 Nonparametric

(84.8, 99.3, 98.6)

(84.5, 99.3, 98.5)

(86.5, 99.2, 98.5)

(85.9, 99.1, 98.4)

 

Classical

    
 

 Dixon

(51.5, 94.6, 92.4)

(63.0, 94.6, 93.0)

(73.0, 94.6, 93.5)

(72.6, 94.6, 93.5)

 

 Grubbs

(70.7, 90.0, 89.0)

(77.0, 90.0, 89.4)

(82.3, 90.0, 89.6)

(82.0, 90.1, 89.7)

 

Projection Quantile

    

5

 Constant

(89.2, 99.6, 99.1)

(40.0, 99.5, 96.5)

(35.9, 97.9, 94.8)

(35.0, 97.9, 94.8)

 

 Linear

(89.0, 99.6, 99.1)

(87.3, 99.5, 98.9)

(85.5, 97.5, 96.9)

(84.6, 97.6, 96.9)

 

 Nonlinear

(89.0, 99.6, 99.1)

(87.3, 99.5, 98.9)

(87.2, 99.3, 98.7)

(86.2, 99.2, 98.6)

 

 Nonparametric

(84.1, 99.4, 98.6)

(84.2, 99.3, 98.5)

(86.9, 99.0, 98.4)

(86.0, 99.0, 98.4)

 

Classical

    
 

 Dixon

(66.0, 94.4, 92.9)

(73.3, 94.4, 93.3)

(79.6, 94.4, 93.6)

(79.9, 94.5, 93.8)

 

 Grubbs

(81.1, 90.0, 89.6)

(82.9, 90.0, 89.7)

(86.1, 90.0, 89.8)

(86.0, 90.2, 90.0)

 

Projection Quantile

    

6

 Constant

(87.6, 99.6, 99.0)

(34.1, 99.6, 96.4)

(29.7, 98.2, 94.8)

(29.7, 98.4, 94.9)

 

 Linear

(87.4, 99.6, 99.0)

(85.9, 99.5, 98.8)

(82.5, 97.9, 97.1)

(82.7, 98.0, 97.2)

 

 Nonlinear

(87.4, 99.6, 99.0)

(85.9, 99.5, 98.8)

(85.7, 99.3, 98.1)

(85.0, 99.2, 98.5)

 

 Nonparametric

(82.8, 99.3, 98.5)

(83.4, 99.3, 98.5)

(86.0, 99.2, 98.6)

(85.8, 99.1, 98.5)

 

Classical

    
 

 Dixon

(73.2, 94.3, 93.2)

(78.4, 94.3, 93.5)

(83.5, 94.3, 93.7)

(83.6, 94.3, 93.8)

 

 Grubbs

(85.8, 90.0, 89.8)

(86.5, 90.1, 89.9)

(88.2, 90.1, 90.0)

(88.0, 90.2, 90.0)

 

Projection Quantile

    

7

 Constant

(86.2, 99.6, 99.0)

(30.2, 99.8, 96.3)

(26.3, 98.6, 95.0)

(26.1, 98.6, 95.0)

 

 Linear

(85.8, 99.6, 98.9)

(85.6, 99.5, 98.8)

(81.4, 98.3, 97.5)

(80.4, 98.3, 97.4)

 

 Nonlinear

(85.8, 99.6, 98.9)

(85.6, 99.4, 98.7)

(85.9, 99.5, 98.8)

(84.7, 99.3, 98.6)

 

 Nonparametric

(80.8, 99.3, 98.4)

(82.3, 99.3, 98.5)

(86.2, 99.2, 98.6)

(85.8, 99.2, 98.5)

 

Classical

    
 

 Dixon

(71.2, 94.5, 93.4)

(76.7, 94.5, 93.6)

(82.4, 94.5, 93.9)

(82.7, 94.5, 93.9)

 

 Grubbs

(89.1, 90.0, 90.0)

(87.7, 90.0, 89.9)

(89.2, 90.0, 90.0)

(89.3, 90.0, 89.9)

 

Projection Quantile

    

8

 Constant

(85.9, 99.7, 99.0)

(26.5, 99.8, 96.1)

(23.2, 98.0, 94.2)

(24.1, 97.9, 94.2)

 

 Linear

(85.7, 99.6, 98.9)

(84.8, 99.4, 98.7)

(77.1, 98.1, 97.0)

(77.3, 98.1, 97.1)

 

 Nonlin

(85.7, 99.6, 98.9)

(84.8, 98.8, 98.1)

(84.4, 99.4, 98.7)

(84.0, 99.3, 98.5)

 

 Nonparametric

(80.2, 99.4, 98.4)

(81.6, 99.3, 98.4)

(85.7, 99.2, 98.5)

(86.2, 99.1, 98.5)