Bayesian estimators and highest posterior density credible intervals are obtained for two popular inequality measures, viz. the Gini index and the Bonferroni index in the case of the Dagum distribution. The study considers informative and non-informative priors, i.e. the Mukherjee-Islam prior...

Bayesian estimators and highest posterior density credible intervals are obtained for two popular inequality measures, viz. the Gini index and the Bonferroni index in the case of the Dagum distribution. The study considers informative and non-informative priors, i.e. the Mukherjee-Islam prior...

In this paper, we studied estimators based on an interval shrinkage with equal weights point shrinkage estimators for all individual target points ¯θ ∈ (θ0,θ1) for exponentially distributed observations in the presence of outliers drawn from a uniform distribution. Estimators...

This paper applies LINEX loss functions to forecasting nonlinear functions of variance. We derive the optimal one-step-ahead LINEX forecast for various volatility models using data transformations such as ln(y2t) where yt is the return of the asset. Our results suggest that the LINEX loss...

In this paper, we studied estimators based on an interval shrinkage with equal weights point shrinkage estimators for all individual target points ¯θ ∈ (θ0,θ1) for exponentially distributed observations in the presence of outliers drawn from a uniform distribution. Estimators obtained from...

Based on a record sample from the Rayleigh model, we consider the problem of estimating the scale and location parameters of the model and predicting the future unobserved record data. Maximum likelihood and Bayesian approaches under different loss functions are used to estimate the model's...

Based on a record sample from the Rayleigh model, we consider the problem of estimating the scale and location parameters of the model and predicting the future unobserved record data. Maximum likelihood and Bayesian approaches under different loss functions are used to estimate the model's...