A variance shift model for detection of outliers in the linear measurement error model (Q1724031)

Summary: We present a variance shift model for a linear measurement error model using the corrected likelihood of \textit{T. Nakamura} [Biometrika 77, No. 1, 127--137 (1990; Zbl 0691.62066)]. This model assumes that a single outlier arises from an observation with inflated variance. The corrected likelihood ratio and the score test statistics are proposed to determine whether the \(i\)th observation has an inflated variance. A parametric bootstrap procedure is used to obtain empirical distributions of the test statistics and a simulation study has been used to show the performance of proposed tests. Finally, a real data example is given for illustration.