References
- Azzalini, A. (1985). A class of distribution which includes the normal ones, Scandinavian Journal of Statistics, 33, 561-574.
- Azzalini, A. and Dalla-Valle, A. (1996). The multivariate skew normal distribution, Biometrika, 83, 715-726. https://doi.org/10.1093/biomet/83.4.715
- Bickel, P. J. and Doksum, K. A. (1981). An analysis of transformations revisited, Journal of American Statistical Association, 76(374), 296-311. https://doi.org/10.1080/01621459.1981.10477649
- Cabral, C. S., Lachos, V. H. and Prates, M. O. (2012). Multivariate mixture modeling using skew-normal independent distribution, Computational Statistics and Data Analysis, 56, 126-142. https://doi.org/10.1016/j.csda.2011.06.026
- Cook, R. D. and Weisberg, S. (1994). An Introduction to Regression Graphics, 56, Wiley, New York.
- Ho, H. J., Lin, T. I., Chen, H.-Y. and Wang, W.-L. (2012). Some results on the truncated multivariate t distribution, Journal of Statistical Planning & Inference, 142, 25-40. https://doi.org/10.1016/j.jspi.2011.06.006
- Kim, H. J. (2008). Moments of truncated Student-t distribution, Journal of Korean Statistical Society, 37, 81-87. https://doi.org/10.1016/j.jkss.2007.06.001
- Kim, S.-G. (2012). ECM Algorithm for fitting of mixtures of multivariate Skew t-Distribution, Communications of the Korean Statistical Society, 19, 673-684. https://doi.org/10.5351/CKSS.2012.19.5.673
- Lachos, V. H., Ghosh, P. and Arellano-Valle, R. B. (2010). Likelihood based inference for skew-normal independent linear mixed model, Statistica Sinica, 20, 303-322.
- Lin, T.-I. (2010). Robust mixture modeling using multivariate skew t distributions, Statistics and Computing, 20, 343-356. https://doi.org/10.1007/s11222-009-9128-9
- Lo, K., Brinkman, R. R. and Gottardo, R. (2008). Automated gating of ow cytometry data via robust model-based clustering. Cytometry Part A, 73, 321-332.
- Lo, K. and Gottardo, R. (2012). Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: An alternative to the skew-t distribution, Statistics and Computing, 22, 33-52. https://doi.org/10.1007/s11222-010-9204-1
- McLachlan, G. J. and Peel, D. (2000). Finite Mixture Models, Wiley, New York.
- Pyne, S., Hu, X., Wang, K., Rossin, E., Lin, T. I., Maier, L., Baecher-Allan, C., McLachlan, G. J., Tamayo, P., Ha er, D. A., De Jager, P. L. and Mesirov, J. P. (2009). Automated high-dimensional ow cytometric data analysis, Proceedings of the National Academy of Sciences of the United States of America, 106, 8519-8524. https://doi.org/10.1073/pnas.0903028106
- Sahu, S. K., Dey, D. K. and Branco, M. D. (2003). A new class of multivariate skew distribution with application to Bayesian regression model, The Canadian Journal of Statistics, 31, 129-150. https://doi.org/10.2307/3316064
Cited by
- An Alternating Approach of Maximum Likelihood Estimation for Mixture of Multivariate Skew t-Distribution vol.27, pp.5, 2014, https://doi.org/10.5351/KJAS.2014.27.5.819