TY - JOUR
JF - JIRSS
JO - JIRSS
VL - 16
IS - 1
PY - 2017
Y1 - 2017/6/01
TI - On the Finite Mixture Modeling via Normal Mean-Variance Birnbaum-Saunders Distribution
TT - On the Finite Mixture Modeling via Normal Mean-Variance Birnbaum-Saunders Distribution
N2 - This paper presents a new finite mixture model using the normal mean-variance mixture of Birnbaum-Saunders distribution. The proposed model is multi-modal with wider ranges of skewness and kurtosis. Moreover, it is useful for modeling highly asymmetric data in various theoretical and applied statistical problems. The maximum likelihood estimates of the parameters of the model are computed iteratively by feasible EM algorithm. To illustrate the finite sample properties and performance of the estimators, we conduct a simulation study and illustrate the usefulness of the new model by analyzing a real dataset.
SP - 33
EP - 51
AU - Naderi, Mehrdad
AU - Arabpour, Alireza
AU - Jamalizadeh, Ahad
AD -
KW - Birnbaum-Saunders distribution
KW - ECM-algorithm
KW - Finite mixture model
KW - Mean-variance mixture distribution.
UR - http://jirss.irstat.ir/article-1-724-fa.html
DO - 10.18869/acadpub.jirss.16.1.1003
ER -