Traditional methods for structural uncertainty problems with nonconventional distributions
involve a significant computational burden, attributed to the nonlinear increase of structures …

Hierarchical Bayesian modeling is beneficial when complex models with many parameters
of the same type, such as item response theory (IRT) models, are to be estimated with …

Estimating poverty and inequality parameters for small sub-populations with adequate
precision is often beyond the reach of ordinary survey-weighted methods because of small …

Given the sentence “On sunny days, Rose rides to work with her…”, it is likely that you
predict the word “bicycle” before reading it. Notably, not only adults, but even children from …

We propose a Small Area Estimation model based on Generalized Additive Models for
Location, Scale and Shape (SAE-GAMLSS), for the estimation of household economic …

The study proposes to consider factorial design at three levels and identify all significant
factors based on its inherent strength. The methodology considers full, fractional, and …

The study proposes to consider factorial design at three levels and identify all significant
factors based on its inherent strength. The methodology considers full, fractional, and …

Given the sentence “On sunny days, Rose rides to work with her…”, it is likely that you
predict the word “bicycle” before reading it. Notably, not only adults, but even children from …

In this paper, we consider the problem of producing estimates of poverty and inequality
measures using a Bayesian unit-level small area model, specified on the logarithmic …

Bayesian inference for quantiles of a log-normal variable in presence of censored observations
Page 1 Bayesian inference for quantiles of a log-normal variable in presence of censored …