1 |
Balakrishnan N and Pal S (2012). EM algorithm-based likelihood estimation for some cure rate models, Journal of Statistical Theory and Practice, 6, 698-724.
DOI
|
2 |
Balakrishnan N and Pal S (2013). Lognormal lifetimes and likelihood-based inference for flexible cure rate models based on COM-Poisson family, Computational Statistics and Data Analysis, 67, 41-67.
DOI
|
3 |
Balakrishnan N and Pal S (2015a). Likelihood inference for flexible cure rate models with gamma lifetimes, Communications in Statistics-Theory and Methods, 44, 4007-4048.
DOI
|
4 |
Balakrishnan N and Pal S (2015b). An EM algorithm for the estimation of flexible cure rate model parameters with generalized gamma lifetime and model discrimination using likelihood- and information-based methods, Computational Statistics, 30, 151-189.
DOI
|
5 |
Balakrishnan N and Pal S (2016). Expectation maximization-based likelihood inference for flexible cure rate models with Weibull lifetimes, Statistical Methods in Medical Research, 25, 1535-1563.
DOI
|
6 |
Balakrishnan N, Koutras MV, Milienos F, and Pal S (2016). Piecewise linear approximations for cure rate models and associated inferential issues, Methodology and Computing in Applied Probability, 18, 937-966.
DOI
|
7 |
Chen MH, Ibrahim JG, and Sinha D (1999). A new Bayesian model for survival data with a surviving fraction, Journal of the American Statistical Association, 94, 909-919.
DOI
|
8 |
Cook RD (1986). Assessment of local influence, Journal of the Royal Statistical Society Series B (Methodological), 48, 133-169.
DOI
|
9 |
Cooner F, Banerjee S, Carlin BP, and Sinha D (2007). Flexible cure rate modeling under latent activation schemes, Journal of the American Statistical Association, 102, 560-572.
DOI
|
10 |
Cooray K and Ananda MMA (2008). A generalized of the half-normal distribution with applications to lifetime data, Communications in Statistics - Theory and Methods, 37, 1323-1337.
|
11 |
Fachini JB, Ortega EMM, and Cordeiro GM (2014). A bivariate regression model with cure fraction, Journal of Statistical Computation and Simulation, 84, 1580-1595.
DOI
|
12 |
Flajolet P and Odlyzko A (1990). Singularity analysis of generating functions, SIAM Journal on Discrete Mathematics, 3, 216-240.
DOI
|
13 |
Gradshteyn IS and Ryzhik IM (2000). Table of Integrals, Series and Products(6th ed), Academic Press, San Diego, CA.
|
14 |
Hashimoto EM, Cordeiro GM, Ortega EMM (2013). The new Neyman type A beta Weibull model with long-term survivors, Computational Statistics, 28, 933-954.
DOI
|
15 |
Ibrahim JG, Chen MH, and Sinha D (2001). Bayesian Survival Analysis, Springer, New York.
|
16 |
Maller RA and Zhou X (1996). Survival Analysis with Long-Term Survivors, John Wiley & Sons, New York.
|
17 |
Martinez EZ, Achcar JA, Jacome AAA, and Santos JS (2013). Mixture and non-mixture cure fraction models based on the generalized modified Weibull distribution with an application to gastric cancer data, Computer Methods and Programs in Biomedicine, 112, 343-355.
DOI
|
18 |
Nadarajah S, Cordeiro GM, and Ortega EMM (2015). The Zografos-Balakrishnan-G family of distributions: mathematical properties and applications, Communications in Statistics - Theory and Methods, 44, 186-215.
DOI
|
19 |
Nadarajah S and Kotz S (2006). The beta exponential distribution, Reliability Engineering and System Safety, 91, 689-697.
DOI
|
20 |
Ortega EMM, Cordeiro GM, Campelo AK, Kattan MW, and Cancho VG (2015). A power series beta Weibull regression model for predicting breast carcinoma, Statistics in Medicine, 34, 1366-1388.
DOI
|
21 |
Ortega EMM, Cordeiro GM, and Kattan MW (2012). The negative binomial-beta Weibull regression model to predict the cure of prostate cancer, Journal of Applied Statistics, 39, 1191-1210.
DOI
|
22 |
Ristic MM and Balakrishnan N (2012). The gamma-exponentiated distribution, Journal of Statistical Computation and Simulation, 82, 1191-1206.
DOI
|
23 |
Rodrigues J, Cancho VG, de Castro M, and Louzada-Neto F (2009). On the unification of the longterm survival models, Statistics and Probability Letters, 79, 753-759.
DOI
|
24 |
Tsodikov AD, Ibrahim JG, and Yakovlev AY (2003). Estimating cure rates from survival data: an alternative to two-component mixture models, Journal of the American Statistical Association, 98, 1063-1078.
DOI
|
25 |
Yakovlev AY and Tsodikov AD (1996). Stochastic Models of Tumor Latency and Their Biostatistical Applications, World Scientific Publishing, Singapore.
|
26 |
Zhu H, Ibrahim JG, Lee S, and Zhang H (2007). Perturbation selection and influence measures in local influence analysis, The Annals of Statistics, 35, 2565-2588.
DOI
|
27 |
Zografos K and Balakrishnan N (2009). On families of beta-and generalized gamma-generated distributions and associated inference, Statistical Methodology, 6, 344-362.
DOI
|