Measurement error (errors-in-variables) models are frequently used in various scientific fields, such as engineering, medicine, chemistry, etc. In this work, we consider a new replicated structural measurement error model in which the replicated observations jointly follow scale mixtures of...

Heteroscedasticity checking in regression analysis plays an important role in modelling. It is of great interest when random errors are correlated, including autocorrelated and partial autocorrelated errors. In this paper, we consider multivariate <italic>t</italic> linear regression models, and construct the...

Recently Lin & Wei (2003) developed the score test for heteroscedasticity in nonlinear regression models and investigated the power of this test through Monte Carlo simulations. This paper presents an approach for estimating local power of the score test, based on an asymptotic approximation to...