Fig 1.
Probability density functions of the standard PDLomax and RPDLomax distributions at various values of λ.
Fig 2.
Cumulative distribution functions of the standard PDLomax and RPDLomax distributions at various values of λ.
Table 1.
Bias, RMSE and CP calculated for the parameters β0, β1, and λ.
Table 2.
Mean proportion of 1’s, for λ = {0.25, 0.5, 2, 4}, of the samples of the power Cauchy model.
Table 3.
Comparative Bayesian measures of the proposed models and binary logistic regression.
Table 4.
Descriptive measures of the Wilt dataset.
SD = standard deviation.
Table 5.
Comparison metrics of the models fitted to the Wilt dataset.
Table 6.
Descriptive measures of the parameters of the RPDLomax model fitted to the Wilt dataset.
Fig 3.
Nonlinear effect of each variable on the probability that a tree is diseased (), on average, when the other variables are constant, based on the adjusted RPDLomax model (Wilt dataset).
Fig 4.
Density of the predictive probabilities estimated by the RPDLomax model adopted in the first application (Wilt dataset), for observations #200 to 220.
The red line represents the average of the estimated diseased tree probabilities, .
Fig 5.
Plots of the quantile residuals of the RPDLomax model fitted to the Wilt dataset.
Fig 6.
Boxplots of the estimated mean predictive probabilities for each observation, based on the RPDLomax model and the Logistic model for each class (Wilt dataset).
Table 7.
Descriptive statistics (minimum, first quartile, median, mean, third quartile, maximum) of probabilities for the RPDLomax and Logistic models by class (Wilt dataset).
Table 8.
Descriptive measures of the Blood Donation dataset.
Table 9.
Comparison metrics of the models fitted to the Blood Donation dataset.
Table 10.
Descriptive measures of the parameters of the RPDLomax fitted to the Blood Donation dataset.
Fig 7.
Plots of the quantile residuals of the RPDLomax model fitted to the Blood Donation dataset.
Fig 8.
Boxplots of the estimated mean predictive probabilities for each observation, based on the RPDLomax model and the Logistic model for each class (Blood Donation dataset).