Likelihood ratio test change-point detection in the skew slash distribution

References

• Arellano-Valle, R. B., L. M. Castro, and R. H. Loschi. 2013. Change point detection in the skew-normal model parameters. Communications in Statistics - Theory and Methods 42 (4):603–18. doi:10.1080/03610926.2011.611321.
   Web of Science ®Google Scholar
• Arslan, O. 2008. An alternative multivariate skew slash distribution. Statistics & Probability Letters 78 (16):2756–61. doi:10.1016/j.spl.2008.03.017.
   Web of Science ®Google Scholar
• Arslan, O. 2009. Maximum likelihood parameter estimation for the multivariate skew slash distribution. Statistics & Probability Letters 79 (20):2158–65. doi:10.1016/j.spl.2009.07.009.
   Web of Science ®Google Scholar
• Arslan, O., and A. I. Genc. 2009. A generalization of the multivariate slash distribution. Journal of Statistical Planning and Inference 139 (3):1164–70. doi:10.1016/j.jspi.2008.07.007.
   Web of Science ®Google Scholar
• Chen, J. 1998. Testing for a change point in linear regression models. Communications in Statistics - Theory and Methods 27 (10):2481–93. doi:10.1080/03610929808832238.
   Web of Science ®Google Scholar
• Chen, J., and A. K. Gupta. 1997. Testing and locating variance changepoints with application to stock prices. Journal of the American Statistical Association 92 (438):739–47. doi:10.1080/01621459.1997.10474026.
   Web of Science ®Google Scholar
• Chernoff, H., and S. Zacks. 1964. Estimating the current mean of a normal distribution which is subjected to changes in time. The Annals of Mathematical Statistics 35 (3):999–1018. doi:10.1214/aoms/1177700517.
   Google Scholar
• Csörgó, M., and L. Horváth. 1997. Limit theorems in change-point analysis. New York: Wiley.
   Google Scholar
• Gardner, L. A. 1969. On detecting changes in the mean of normal variates. The Annals of Mathematical Statistics 40 (1):116–26. doi:10.1214/aoms/1177697808.
   Google Scholar
• Gomez, H. W., F. A. Quintana, and F. J. Torres. 2007. A new family of slash-distributions with elliptical contours. Statistics & Probability Letters 77 (7):717–25. doi:10.1016/j.spl.2006.11.006.
   Web of Science ®Google Scholar
• Hajrajabi, A., and M. Maleki. 2019. Nonlinear semiparametric autoregressive model with finite mixtures of scale mixtures of skew normal innovations. Journal of Applied Statistics 46 (11):2010–29. doi:10.1080/02664763.2019.1575953.
   Web of Science ®Google Scholar
• Hasan, A., W. Ning, and A. K. Gupta. 2014. An information-based approach to the change-point problem of the noncentral skew t distribution with applications to stock market data. Sequential Analysis 33 (4):458–74. doi:10.1080/07474946.2014.961842.
   Web of Science ®Google Scholar
• Hsu, D. A. 1979. Detecting shifts of parameter in gamma sequences with applications to stock price and air traffic flow analysis. Journal of the American Statistical Association 74 (365):31–40. doi:10.1080/01621459.1979.10481604.
   Web of Science ®Google Scholar
• Liu, Z., and L. Qian. 2009. Changepoint estimation in a segmented linear regression via empirical likelihood. Communications in Statistics - Simulation and Computation 39 (1):85–100. doi:10.1080/03610910903312193.
   Web of Science ®Google Scholar
• Ngunkeng, G., and W. Ning. 2014. Information approach for the change-point detection in the skew normal distribution and its application. Sequential Analysis 33 (4):475–90. doi:10.1080/07474946.2014.961845.
   Web of Science ®Google Scholar
• Page, E. S. 1954. Continue inspection schemes. Biometrika 41 (1-2):100–235. doi:10.2307/2333009.
   Web of Science ®Google Scholar
• Page, E. S. 1955. A test for a chance in a parameter occurring at an unknown point. Biometrika 42 (3-4):523–7. doi:10.2307/2333401.
   Web of Science ®Google Scholar
• Punathumparambath, B. 2013. A new family of skewed slash distributions generated by the Cauchy Kernel. Communications in Statistics - Theory and Methods 42 (13):2351–61. doi:10.1080/03610926.2011.599508.
   Web of Science ®Google Scholar
• Said, K. K., W. Ning, and Y. Tian. 2017. Likelihood procedure for testing changes in skew normal model with applications to stock returns. Communications in Statistics - Simulation and Computation 46 (9):6790–802. doi:10.1080/03610918.2016.1212067.
   Web of Science ®Google Scholar
• Said, K. K., W. Ning, and Y. Tian. 2018. Detecting changes in linear regression models with skew normal errors. Random Operators and Stochastic Equations 26 (1):1–10. doi:10.1515/rose-2018-0001.
   Web of Science ®Google Scholar
• Sen, A., and M. S. Srivastava. 1975. On tests for detecting change in mean. The Annals of Statistics 3 (1):98–108. doi:10.1214/aos/1176343001.
   Web of Science ®Google Scholar
• Tian, W., G. Han, T. Wang, and V. Pipitpojanakarn. 2017. EM estimation for multivariate skew slash distribution. In Robustness in econometrics, 235–48. Cham: Springer.
   Google Scholar
• Tian, W., T. Wang, and A. K. Gupta. 2018. A new family of multivariate skew slash distribution. Communications in Statistics - Theory and Methods 47 (23):5812–24. doi:10.1080/03610926.2017.1402049.
   Web of Science ®Google Scholar
• Wang, J., and M. G. Genton. 2006. The multivariate skew slash distribution. Journal of Statistical Planning and Inference 136 (1):209–20. doi:10.1016/j.jspi.2004.06.023.
   Web of Science ®Google Scholar
• Worsley, K. J. 1979. On the likelihood ratio test for a shift in location of normal populations. Journal of the American Statistical Association 74 (366):365–7. doi:10.2307/2286336.
   Web of Science ®Google Scholar
• Zou, C., Y. Liu, P. Qin, and Z. Wang. 2007. Empirical likelihood ratio test for the change-point problem. Statistics and Probability Letters 77 (4):374–82. doi:10.1016/j.spl.2006.08.003.
   Web of Science ®Google Scholar