GLDreg : Fit GLD Regression/Quantile/AFT Model to Data

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Abstract

Owing to the rich shapes of Generalised Lambda Distributions (GLDs), GLD standard/quantile/Accelerated Failure Time (AFT) regression is a competitive flexible model compared to standard/quantile/AFT 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. For AFT model, it also eliminates the needs to try several different AFT models, owing to the flexible shapes of GLD. The goodness of fit of the proposed model can be assessed via QQ plots and Kolmogorov-Smirnov tests and data driven smooth 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. References include the following: Su (2015) "Flexible Parametric Quantile Regression Model" , Su (2021) "Flexible parametric accelerated failure time model".

Salvato in:
Autori: Steve Yu Shuo Su iD; R Core Team
Data di pubblicazione:11/11/2014
Tipo di documento:Dataset
Lingua:inglese
DOI: 10.32614/cran.package.gldreg
Accesso aperto: Accesso aperto Gold: rivista ad accesso aperto – Testo completo ad accesso aperto (licenza: CC-BY-NC-SA, versione editoriale)
Soggetti:
Statistical Distribution Estimation and Applications (Physical Sciences > Mathematics > Statistics and Probability)
Advanced Statistical Methods and Models (Physical Sciences > Mathematics > Statistics and Probability)
Statistical Methods and Inference (Physical Sciences > Mathematics > Statistics and Probability)
quantile regression, accelerated failure time model, robust regression, outlier robustness, Q-Q plots, Kolmogorov-Smirnov test, smooth tests, goodness of fit, simulation-based inference, interval estimation
Identificativi: OpenAlex W4399649695

Dati dell'indice centrale: OpenAlex (licenza CC0).

Riassunto:Owing to the rich shapes of Generalised Lambda Distributions (GLDs), GLD standard/quantile/Accelerated Failure Time (AFT) regression is a competitive flexible model compared to standard/quantile/AFT 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. For AFT model, it also eliminates the needs to try several different AFT models, owing to the flexible shapes of GLD. The goodness of fit of the proposed model can be assessed via QQ plots and Kolmogorov-Smirnov tests and data driven smooth 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. References include the following: Su (2015) "Flexible Parametric Quantile Regression Model" , Su (2021) "Flexible parametric accelerated failure time model".
DOI:10.32614/cran.package.gldreg