In this paper, a generalized autoregressive conditional heteroskedasticity model under skew-
normal distributions is studied. A maximum likelihood approach is taken and the parameters …

In statistical diagnostics and sensitivity analysis, the local influence method plays an
important role and has certain advantages over other methods in several situations. In this …

In statistical diagnostics, detecting influential observations is pivotal for assessing model
fitting. To address parameter restrictions while maintaining necessary properties, the …

This paper studies Bayesian local influence analysis for the spatial autoregressive models
with heteroscedasticity (heteroscedastic SAR models). Two local diagnostic procedures …

In this paper, we use the local influence method to study a vector autoregressive model
under Student′ st‐distributions. We present the maximum likelihood estimators and the …

In this paper, we introduce a diagnostic method for identifying influential observations in the
multivariate DCC-GARCH model. We employ the Bayesian local influence method by …

This paper studies the influence diagnostics in meta‐regression model including case
deletion diagnostic and local influence analysis. We derive the subset deletion formulae for …

We study the local influence in the general spatial model which includes the spatial
autoregressive model and the spatial error model as two special cases. The stepwise local …

Future nuclear fuel cycle options may present advantages over today's once-through fuel
cycle. Nuclear fuel cycle simulation tools assess the performance of those fuel cycles as well …