Density Regression Based on Proportional Hazards Family

Entropy

Wei Dang³  Keming Yu²  Carlos Alberto de Bragan๺ Pereira¹ 

[1] id="af1-entropy-17-03679">1Business School, Shihezi University, Xinjiang, 831300, ChinaChina;Business School, Shihezi University, Xinjiang, 831300, China

关键词: best linear unbiased estimators (BLUE);    density regression;    exact inference;    gamma random variable;    proportional hazards distribution family;    regression analysis;   

DOI  :  10.3390/e17063679

来源: mdpi

【 摘 要 】

This paper develops a class of density regression models based on proportional hazards family, namely, Gamma transformation proportional hazard (Gt-PH) model. Exact inference for the regression parameters and hazard ratio is derived. These estimators enjoy some good properties such as unbiased estimation, which may not be shared by other inference methods such as maximum likelihood estimate (MLE). Generalised confidence interval and hypothesis testing for regression parameters are also provided. The method itself is easy to implement in practice. The regression method is also extended to Lasso-based variable selection.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland