A Variance Shift Model for Detection of Outliers in the Linear Measurement Error Model
Keyword(s):
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 theith 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.
2019 ◽
Vol 48
(10)
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pp. 2985-2997
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2019 ◽
Vol 31
(3)
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pp. 549-566
2010 ◽
Vol 80
(8)
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pp. 927-936
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2005 ◽
Vol 10
(1)
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pp. 118-130
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2016 ◽
Vol 11
(1)
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pp. 139-158
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2000 ◽
Vol 27
(4)
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pp. 475-482
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2016 ◽
Vol 15
(2)
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pp. 87-104
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