GLDreg: Fit GLD Regression Model and GLD Quantile Regression Model to Empirical Data. Owing to the rich shapes of GLDs, GLD standard/quantile regression is a competitive flexible model compared to standard/quantile regression. The proposed method has some major advantages: 1) it provides a reference line which is very robust to outliers with the attractive property of zero mean residuals and 2) it gives a unified, elegant quantile regression model from the reference line with smooth regression coefficients across different quantiles. The goodness of fit of the proposed model can be assessed via QQ plots and the Kolmogorov-Smirnov test, to ensure the appropriateness of the statistical inference under consideration. Statistical distributions of coefficients of the GLD regression line are obtained using simulation, and interval estimates are obtained directly from simulated data.

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References in zbMATH (referenced in 2 articles , 1 standard article )

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  1. Su, Steve: Flexible modelling of survival curves for censored data (2016)
  2. Su, Steve: Flexible parametric quantile regression model (2015)