1 |
Lin, T.-I., Lee, J.-C. and Yen, S. Y. (2007a). Finite mixture modeling using the skew normal distributions, Statistica Sinica, 17, 909-927.
|
2 |
Liu, C. and Rubin, D. B. (1994). The ECME algorithm: a simple extension of EM and ECM with fast monotonic convergence, Biometroka, 81, 633-784.
DOI
ScienceOn
|
3 |
McLachlan, G. J. and Peel, D. (2000). Finite Mixture Models, Wiley, New York.
|
4 |
Sahu, S. K., Dey, D. K. and Branco, M. D. (2003). A new class of multivariate skew distribution with application to Bayesian regression molel, The Canadian Journal of Statistics, 31, 129-150.
DOI
ScienceOn
|
5 |
Azzalini, A. (1985). A class of distribution which includes the normal ones, Scandinavian Journal of Statistics, 33, 561-574.
|
6 |
Azzalini, A. and Dalla-Valle, A. (1996). The multivariate skew normal distribution, Biometrika, 83, 715-726.
DOI
ScienceOn
|
7 |
Azzalini, A. and Capitanio, A. (2003). Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t-distribution, Journal of the Royal Statistical Society, series B 65, 367-389.
DOI
ScienceOn
|
8 |
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.
DOI
ScienceOn
|
9 |
Cook, R. D. and Weisberg, S. (1994). An Introduction to Regression Graphics, 56, Wiley, New York.
|
10 |
Lee, S. and McLachlan, G. J. (2011). On the fitting of mixtures of multivariate skew t-distributions via the EM algorithm, Technical Report of University of Queensland, Available from: http://arxiv.org/PScache/arxiv/pdf/1109/1109.4706v1.pdf.
|
11 |
Lin, T.-I. (2010). Robust mixture modeling using multivariate skew t distributions, Statistics and Computing, 20, 343-356.
DOI
|
12 |
Lin, T.-I., Lee, J.-C. and Hsieh, W. J. (2007b). Robust mixture modeling using the skew t distributions, Statistics and Computing, 17, 81-92.
DOI
|