References
- Aalen, O. 1978. Nonparametric inference for a family of counting processes. Annuals of Statistics 6 (4):701–26.
- Akaike, H. 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19 (6):716–723.
- Amemiya, T. 1983. Handbook ofeconometrics. Vol. 1, 1st ed., chapter 6, 333–89. North Holland: Elsevier.
- Anderson, J. A., A. Senthilselvan 1980. Smooth estimates for the hazard function. Journal of the Royal Statistical Society: Series B 42 (3):322–27.
- Bertsekas, D. P. 1982. Projected Newton methods for optimization problems with simple constraints. SIAM Journal on Control and Optimization 20:221–46.
- Breslow, N. E. 1972. Discussion of the paper by D. R. Cox. Journal of the Royal Statistical Society: Series B 34 (2):216–17.
- Chan, R. H., J. Ma 2012. A multiplicative iterative algorithm for box-constrained penalized likelihood image restoration. IEEE Transactions on Image Processing 21:3168–81.
- Chen, Y. H. 2010. Semiparametric marginal regression analysis for dependent competing risks under an assumed copula. Journal of the Royal Statistical Society: Series B 72:235–251.
- Clayton, D. G. 1978. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biomeirika 65 (1):141–151.
- Efron, B. 1967. The two sample problem with censored data. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, Vol. 4 of Berkeley symposium, ed. L. M. L. Cam, and J. Neyman, 831–53. Berkeley: University of California Press.
- Frank, M. J. 1979. On the simultaneous associativity of F(x, y) and x + y − F(x, y). Aequationes Mathematicae 19:194–226.
- Frees, E. W., E. A. Valdez 1998. Understanding relationships using copulas. North American Actuarial Journal 2:1–25.
- Gumbel, E. J. 1961. Distributions des valeurs extrme enplusiers dimensions. Publications Institute Statistical University Pairs 9:171–73.
- Honore, B. E., J. L. Powell 1994. Pairwise difference estimators of censored and truncated regression models. Journal of Econometrics 64:241–78.
- Hougaard, P. 1986. A class of multivariate failure time distribution. Biometrika 73:671–78.
- Huang, X., R. A. Wolfe 2002. A frailty model for informative censoring. Biometrics 58:510–20.
- Huang, X., N. Zhang 2008. Regression survival analysis with an assumed copula for dependent censoring: A sensitivity approach. Biometrics 64:1090–1099.
- Joly, P., D. Commenges, L. Letenneur 1998. A penalized likelihood approach for arbitrarily censored and truncated data: Application to age-specific incidence of dementia. Biometrics 54 (1):185–94.
- Kaplan, E. L., P. Meier 1958. Nonparametric estimation from incomplete observations. Journal of the American Statistical Association 53 (282):457–481.
- Kenneth, R. H., D. M. Serachitopol, B. W. Brown 1999. Hazard function estimations: A simulation study. Statistics in Medicine 18:3075–3088.
- Lagakos, S., J. Williams 1978. Models for censored survival analysis: A cone class of variable-sum models. Biometrika 65(1):181–189.
- Luenberger, D. G. 1984. Linear and nonlinearprogramming. 2nd ed. Addison-Wesley, US: Springer.
- Ma, J. 2010. Positively constrained multiplicative iterative algorithm for maximum penalized likelihood tomographic reconstruction. IEEE Transactions on Nuclear Science 57:181–92.
- Ma, J., S. Heritier, S. Lô 2014. On the maximum penalized likelihood approach for proportional hazard models with right censored survival data. Computational Statistics and Data Analysis 74:42–156.
- Nelsen, R. B. 2006. An introduction to copulas. 2nd ed. New York: Springer.
- Nelson, W. 1972. Theory and applications of hazard plotting for censored failure data. Technometrics 42 (1):12–25.
- O’Sullivan, F. 1988. Fast computation of fully automated log-density and log-hazard estimators. SIAM Journal on Scientific and Statistical Computing 9 (2):363–379.
- Rivest, L., M. Wells 2001. A martingale approach to the copula-graphic estimator for the survival function under dependent censoring. Journal of Multivariate Analysis 79:138–155.
- Schwarz, M., G. Jongbloed, I. Van Keilegom 2013. On the identifiability of copulas in bivariate competing risks models. The Canadian Journal of Statistics 41:291–303.
- Senthilselvan, A. 1987. Penalized likelihood estimation of hazard and intensity functions. Journal of the Royal Statistical Society: Series B 49 (2):170–74.
- Wang, A. 2012. On the nonidentifiability property of Archimedean copula models under dependent censoring. Statistics and Probability Letters 82:621–25.
- Wang, A., K. Chandra, R. Xu, J. Sun 2015. The identifiability of dependent competing risks models induced by bivariate frailty models. Scandinavian Journal of Statistics 42:427–37.
- Wienke, A. 2010. FrailtyModels in Survival Analysis. CRC Biostatistics Series, Boca Raton: Chapman and Hall.
- Yu, Y., D. Ruppert 2002. Penalized spline estimation for partially linear single-index models. Journal of the American Statistical Association 97 (460):1042–54.
- Zheng, M., J. P. Klein 1994. A self-consistent estimator of marginal survival functions based on dependent competing risk data and an assumed copula. Communications in Statistics - Theory and Methods 23 (8):2299–2311.
- Zheng, M., J. P. Klein 1995. Estimate of marginal survival for dependent competing risks based on an assumed copula. Biometrika 82 (1):127–38.