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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)