The geometric power half-normal regression model with cure rate
Abstract
In this paper we consider the geometric cure rate model defined in [16], using for $S_0(\cdot)$, the survival function of carcinogenic cells, an extension of the half-normal distribution based on the distribution of the maximum of a random sample. The implementation of maximum likelihood estimation for the model parameters is discussed and, nally, the model is fitted to a real database (Melanoma data set), and comparisons are performed with alternatives to the new $S_0(\cdot)$.
Keywords
References
- Akaike, H. (1974). A new look at the statistical model identication. IEEE Transactions of Automatic Control, 19(6), 716-723.
- Berkson, J., Gage, R. (1952). Survival curve for cancer patients following treatment. Journal of the American Statistical Association, 47, 501-515.
- Boag, J.W. (1949). Maximum likelihood estimates of the proportion of patients cured by cancer therapy. Journal of the Royal Statistical Society B, 11,15-53.
- Cancho, V.G., Louzada, F., Barriga, G.D.C. (2011) The Geometric Birnbaum-Saunders regression model with cure rate. Journal of Statistical Planning an Inference, 142, 993-1000.
- Cooray, K. and Ananda, M.M.A. (2008). A Generalization of the Half-Normal Distribution with Applications to Lifetime Data. Communications in Statistics - Theory and Methods, 37, 1323-1337.
- Durrans, S.R. (1992). Distributions of fractional order statistics in hydrology. Water Resources Research, 28, 16491655.
- Gómez, Y.M., Bolfarine, H. (2015). Likelihood-based inference for power half-normal distri- bution. Journal of Statistical Theory and Applications, 14, 383398.
- Gupta, D. and Gupta, R.C. (2008). Analyzing skewed data by power normal model. Test, 17, 197210.
Details
Primary Language
English
Subjects
Mathematical Sciences
Journal Section
Research Article
Publication Date
April 1, 2018
Submission Date
April 1, 2016
Acceptance Date
June 22, 2016
Published in Issue
Year 2018 Volume: 47 Number: 2