Improved Inference for Moving Average Disturbances in Nonlinear Regression Models
This paper proposes an improved likelihood-based method to test for first-order moving average in the disturbances of nonlinear regression models. The proposed method has a third-order distributional accuracy which makes it particularly attractive for inference in small sample sizes models. Compared...
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Main Author: | Pierre Nguimkeu |
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Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
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Series: | Journal of Probability and Statistics |
Online Access: | http://dx.doi.org/10.1155/2014/207087 |
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