Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/11997
Title: Density Regression Based on Proportional Hazards Family
Authors: Dang, W
Yu, K
Keywords: Best linear unbiased estimators (BLUE);Density regression;Exact inference;Gamma random variable;Proportional hazards distribution family;Regression analysis
Issue Date: 2015
Publisher: MDPI
Citation: Entropy,17, (6): pp. 3679 - 3691, (2015)
Abstract: 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.
URI: http://www.mdpi.com/1099-4300/17/6/3679
http://bura.brunel.ac.uk/handle/2438/11997
DOI: http://dx.doi.org/10.3390/e17063679
ISSN: 1099-4300
Appears in Collections:Dept of Mathematics Research Papers

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