Multivariate Type Distributions Research Articles

A Generalization of Burr Type XII Distribution with Properties, Copula and Modeling Symmetric and Skewed Real Data Sets

A new generalization of Burr type XII model is introduced and studied. The genesis of the new model is based on the family of Cordeiro et al. (2016). The new model generalizes at least eight important sub-models. The new density can be unimodal, symmetric and left skewed. Some useful properties related to the new model are derived. The Clayton Copula-based construction is used to generate many bivariate and multivariate type distributions. Graphically, we performed the simulation experiments to assess of the finite sample behavior of the estimations.

Expanding the Nadarajah Haghighi Model: Copula, Censored and Uncensored Validation, Characterizations and Applications

A new three-parameter Nadarajah Haghighi model is introduced and studied. The new density has various shapes such as the right skewed, left skewed and symmetric and its corresponding hazard rate shapes can be increasing, decreasing, bathtub, upside down and constant. Characterization results are obtained based on two truncated moments and in terms of the hazard function. Validation via a modified chi-squared goodness-of-fit test is presented under the new model. A simple type Copula based construction is employed in deriving many bivariate and multivariate type distributions. The potentiality uncensored and censored real data sets. We constructed a modified Nikulin-Rao-Robson chi-square goodness-of-fit type test for the new model. This modi…ed chi-square test takes into account both unknown parameters and censorship. Validation in case of right censoring and all the elements constituting the test criteria. The censored aluminum reduction cells data is analyzed for validation.

A novel four-parameter log-logistic model: mathematical properties and applications to breaking stress, survival times and leukemia data

In this paper, we introduce a new continuous log-logistic extension. Several of its properties are established. A numerical analysis for skewness and kurtosis is presented. The new failure rate can be "bathtub or U shaped", "increasing", "decreasing-constant", "J shaped", "constant" and "decreasing". Many bivariate and Multivariate type distributions are derived using the Clayton Copula and the Morgenstern family. To assess of the finite sample behavior of the estimators, we performed a graphical simulation. Some useful applications are considered for supporting the new model.

A Generalization of Binomial Exponential-2 Distribution: Copula, Properties and Applications

In this paper, we propose a new three-parameter lifetime distribution for modeling symmetric real-life data sets. A simple-type Copula-based construction is presented to derive many bivariate- and multivariate-type distributions. The failure rate function of the new model can be “monotonically asymmetric increasing”, “increasing-constant”, “monotonically asymmetric decreasing” and “upside-down-constant” shaped. We investigate some of mathematical symmetric/asymmetric properties such as the ordinary moments, moment generating function, conditional moment, residual life and reversed residual functions. Bonferroni and Lorenz curves and mean deviations are discussed. The maximum likelihood method is used to estimate the model parameters. Finally, we illustrate the importance of the new model by the study of real data applications to show the flexibility and potentiality of the new model. The kernel density estimation and box plots are used for exploring the symmetry of the used data.

A New Flexible Three-Parameter Model: Properties, Clayton Copula, and Modeling Real Data

In this article, we introduced a new extension of the binomial-exponential 2 distribution. We discussed some of its structural mathematical properties. A simple type Copula-based construction is also presented to construct the bivariate- and multivariate-type distributions. We estimated the model parameters via the maximum likelihood method. Finally, we illustrated the importance of the new model by the study of two real data applications to show the flexibility and potentiality of the new model in modeling skewed and symmetric data sets.