this paper is concerned with the problem of finding the minimax estimators of the scale parameter ? in a family of transformed chi-square distributions, under asymmetric squared log error (sle) and modified linear exponential (mlinex) loss functions, using the lehmann theorem [2]. also we show that the results of podder et al. [4] for pareto distribution are a special case of our results for th...

 In this paper, we consider a flexible skew-generalized normal distribution. This distribution is denoted by $FSGN(/lambda _1, /lambda _2 /theta)$. It contains the normal, skew-normal (Azzalini, 1985), skew generalized normal (Arellano-Valle et al., 2004) and skew flexible-normal (Gomez et al., 2011) distributions as special cases. Some important properties of this distribution are establi...

Much work has been done in the area of cluster weighted model (CWM), which extends finite mixture regression to include modelling covariates. Although many types distributions have considered for both response(s) and covariates, our knowledge skewed not yet this paradigm. Herein, a family 24 novel CWMs is allows responses covariates be modelled using one four (the generalized hyberbolic three i...

A finite mixture of normal distributions, in both mean and variance parameters, is a typical finite mixture in the location and scale families. Because the likelihood function is unbounded for any sample size, the ordinary maximum likelihood estimator is not consistent. Applying a penalty to the likelihood function to control the estimated component variances is thought to restore the optimal p...

Formulas are derived for the Gini, Theil and Pietra coefficients a population-weighted mixture of double Pareto–lognormal (dPLN) distributions; they applied to South America 2 years. Results also provided special case lognormal distributions. The formulas useful measuring regional or global inequality in large-scale projects that utilise dPLN distributions their cases.

We present a proposal to deal with the non-normality issue in context of regression models measurement errors when both response and explanatory variable are observed error. W...