References
- Akritas, M.G., Torbeyns, A.F. (1997). Pearson-type goodness-of-fit tests for regression. Can. J. Statist. 25:359–374.
- Bagdonavicius, V., Nikulin, M. (2002). Accelerated Life Models. Modeling and Statistical Analysis. Boca Raton, London, New York, Washington:Chapman and Hall/CRC.
- Bagdonavicius, V., Nikulin, M. (2011). Chi-squared tests for general composite hypotheses from censored samples. Comptes Rendus Mathematique, Ser. I, 349(3–4): 219–223.
- Bagdonavicius, V., Nikulin, M. (2011). Chi-squared goodness-of-fit test for right censored data. Int. J. Appl. Math. Statist. 24:30–50.
- Bagdonavicius, V., Kruopis, J., Nikulin, M. (2011). Nonparametric Tests for Censored Data. London:ISTE & J. Wiley.
- F. de Gusmão, F. R.S., Edwin, M., Gauss, M., Cordeiro, M. (2009). The generalized inverse Weibull distribution. Statist. Pap. 52:591–619.
- Gray, R.J., Pierce, D.A. (1985). Goodness of fit tests for censored survival data. Ann. Statist. 13:552–563.
- Habib, M.G., Thomas, D.R. (1986). Chi-squared goodness-of-fit tests for randomly censored data. Ann. Statist. 14:759–765.
- Hjort, N.L. (1990). Goodness of fit tests in models for life history data based on cumulative hazard rates. Ann. Statist. 18:1221–1258.
- Hollander, M., Pena, E. (1992). Chi-square goodness-of-fit test for randomly censored data. JASA 87(417): 458–463.
- Lawless, J.F. (2003). Statistical Models and Methods for Lifetime Data.2nd ed. New York:Wiley.
- Nikulin, M.S. (1973a). Chi-squared test for normality. Proc. Int. Vilnius Conf. Probab. Theor. Mathemat. Statist. 2:119–122.
- Nikulin, M.S. (1973b). Chi-squared test for continuous distributions with shift and scal parameters. Theor. Probab. Aplic. 18:559–568.
- Nikulin, M.S. (1973c). On a Chi-squared test for continuous distributions. Theor. Probab. Applic. 18(3): 638–639.
- Voinov, V., Nikulin, M., Balakrishnan, N. (2013). Chi-Squared Goodness of Fit Tests with Applications. Amesterdam, Bosten:Elsevier.
- Pena, E. (1998a). Smooth goodness-of-fit tests for composite hypothesis in hazard based models. Ann. Statist. 26:1935–1971.
- Pena, Edsel, (1998b). Smooth goodness-of-fit tests for the baseline hazard in Cox’s proportional hazards model. J. Amer. Stat. Assoc. 93(442): 673–692.
- Ravi, V., Gilbert, P.D. (2009). BB: An R package for solving a large system of nonlinear equations and for optimizing a high-dimensional nonlinear objective function. J. Statist. Software, 32(4).
- Zhang, B. (1999). A chi-squared goodness of-fit test for logistic regression models based on case-control data. Biometrika 86:531–539.