In unit-level small area estimation (SAE), the commonly used nested error regression (NER) model assumes normality which is not always case. To handle non-normal data, researchers in statistics have developed a novel approach using exchangeable and extendible copula called multivariate (MEC) model. This study compares performance of parametric MEC NER models estimating sub-district average per ...

We explain how invariance in distribution under separate or joint contractions, permutations, or rotations can be defined in a natural way for d-dimensional arrays of random variables. In each case, the distribution is characterized by a general representation formula, often easy to state but surprisingly complicated to prove. Comparing the representations in the first two cases, one sees that ...

We extend Stein’s celebrated Wasserstein bound for normal approximation via exchangeable pairs to the multi-dimensional setting. As an intermediate step, we exploit symmetry of obtain error smooth test functions. also a continuous version in terms fourth moments. apply main results multivariate approximations Wishart matrices size n and degree d, where optimal convergence rate n3/d under only m...

In this paper we develop a framework for multivariate functional approximation by suitable Gaussian process via an exchangeable pairs coupling that satisfies approximate linear regression property, thereby building on work Barbour (1990) and Kasprzak (2020). We demonstrate the applicability of our results applying them to joint subgraph counts in Erd?s-Renyi random graph model one hand vectors ...

The COVRATIO statistic has been used to identify the presence of outlier in data, which is based on deletion approach, where determinant covariance matrix for full dataset excludes i-th row. This study proposes a novel discrimination method multivariate normal (MVN) distribution using idea statistic, denoted as . linear function (LDF) MVN will be compared statistic. Simulation results showed th...