Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/238853 
Erscheinungsjahr: 
2018
Quellenangabe: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 11 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2018 [Pages:] 1-14
Verlag: 
MDPI, Basel
Zusammenfassung: 
In survival analysis, the presence of elements not susceptible to the event of interest is very common. These elements lead to what is called a fraction cure, cure rate, or even long-term survivors. In this paper, we propose a unified approach using the negative binomial distribution for modeling cure rates under the Kumaraswamy family of distributions. The estimation is made by maximum likelihood. We checked the maximum likelihood asymptotic properties through some simulation setups. Furthermore, we propose an estimation strategy based on the Negative Binomial Kumaraswamy-G generalized linear model. Finally, we illustrate the distributions proposed using a real data set related to health risk.
Schlagwörter: 
long-term survivors
Kumaraswamy family
survival analysis
negative binomial distribution
generalized linear model
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