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Fig 1.

PDF shapes for the SW baseline distribution.

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Fig 2.

HRF shapes for the SW baseline distribution.

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Fig 3.

Six patterns of the hrf shapes for the SW baseline distribution.

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Fig 4.

TTT plot for the gastric cancer data set.

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Fig 5.

TTT plot for the Alloauto data set.

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Table 1.

Results for the posterior properties of the SW-PH, SL-PH, SG-PH and SEE-PH models.

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Table 1 Expand

Fig 6.

The trace plots of the posterior parameters for the SW-PH model using gastric cancer data.

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Fig 7.

The trace plots of the posterior parameters for the SL-PH model using gastric cancer data.

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Fig 8.

The trace plots of the posterior parameters for the SG-PH model using gastric cancer data.

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Fig 9.

The trace plots of the posterior parameters for the SEE-PH model using gastric cancer data.

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Fig 10.

The autocorrelation plots of the posterior parameters for the SW-PH model using gastric cancer data.

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Fig 11.

The autocorrelation plots of the posterior parameters for the SL-PH model using gastric cancer data.

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Fig 12.

The autocorrelation plots of the posterior parameters for the SG-PH model using gastric cancer data.

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Fig 13.

The autocorrelation plots of the posterior parameters for the SEE-PH model using gastric cancer data.

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Table 2.

Bayesian model comparison for the SW-PH, SL-PH, SG-PH, and SEE-PH models.

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Table 2 Expand

Table 3.

Results for the posterior properties of the SW-PH, SL-PH, SG-PH and SEE-PH models using dataset II.

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Table 3 Expand

Fig 14.

The trace plots of the posterior parameters for the SW-PH model using Alloauto data.

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Fig 14 Expand

Fig 15.

The trace plots of the posterior parameters for the SL-PH model using Alloauto data.

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Fig 16.

The trace plots of the posterior parameters for the SG-PH model using Alloauto data.

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Fig 17.

The trace plots of the posterior parameters for the SEE-PH model using Alloauto data.

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Table 4.

Bayesian model comparison for the SW-PH, SL-PH, SG-PH, and SEE-PH models using Alloauto dataset.

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Table 4 Expand