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A Variance Shift Model for Detection of Outliers in the Linear Measurement Error Model

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  • Babak Babadi
  • Abdolrahman Rasekh
  • Ali Akbar Rasekhi
  • Karim Zare
  • Mohammad Reza Zadkarami

Abstract

We present a variance shift model for a linear measurement error model using the corrected likelihood of Nakamura (1990). 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 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.

Suggested Citation

  • Babak Babadi & Abdolrahman Rasekh & Ali Akbar Rasekhi & Karim Zare & Mohammad Reza Zadkarami, 2014. "A Variance Shift Model for Detection of Outliers in the Linear Measurement Error Model," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-9, September.
    • Handle: RePEc:hin:jnlaaa:396875
    DOI: 10.1155/2014/396875
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