The Laplace Likelihood Ratio Test for Heteroscedasticity
It is shown that the likelihood ratio test for heteroscedasticity, assuming the Laplace distribution, gives good results for Gaussian and fat-tailed data. The likelihood ratio test, assuming normality, is very sensitive to a...
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| Format: | Article |
| Language: | English |
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Wiley
2011-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
| Online Access: | http://dx.doi.org/10.1155/2011/249564 |
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| _version_ | 1849304931230547968 |
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| author | J. Martin van Zyl |
| author_facet | J. Martin van Zyl |
| author_sort | J. Martin van Zyl |
| collection | DOAJ |
| description | It is shown that the likelihood ratio test for heteroscedasticity,
assuming the Laplace distribution, gives good
results for Gaussian and fat-tailed data. The
likelihood ratio test, assuming normality, is
very sensitive to any deviation from normality,
especially when the observations are from a
distribution with fat tails. Such a likelihood
test can also be used as a robust test for a
constant variance in residuals or a time series
if the data is partitioned into
groups. |
| format | Article |
| id | doaj-art-3b13279d81f34974ba74fc145dd2dedf |
| institution | Kabale University |
| issn | 0161-1712 1687-0425 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Mathematics and Mathematical Sciences |
| spelling | doaj-art-3b13279d81f34974ba74fc145dd2dedf2025-08-20T03:55:36ZengWileyInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04252011-01-01201110.1155/2011/249564249564The Laplace Likelihood Ratio Test for HeteroscedasticityJ. Martin van Zyl0Department of Mathematical Statistics and Actuarial Science, University of the Free State, P.O. Box 339, Bloemfontein 9300, South AfricaIt is shown that the likelihood ratio test for heteroscedasticity, assuming the Laplace distribution, gives good results for Gaussian and fat-tailed data. The likelihood ratio test, assuming normality, is very sensitive to any deviation from normality, especially when the observations are from a distribution with fat tails. Such a likelihood test can also be used as a robust test for a constant variance in residuals or a time series if the data is partitioned into groups.http://dx.doi.org/10.1155/2011/249564 |
| spellingShingle | J. Martin van Zyl The Laplace Likelihood Ratio Test for Heteroscedasticity International Journal of Mathematics and Mathematical Sciences |
| title | The Laplace Likelihood Ratio Test for Heteroscedasticity |
| title_full | The Laplace Likelihood Ratio Test for Heteroscedasticity |
| title_fullStr | The Laplace Likelihood Ratio Test for Heteroscedasticity |
| title_full_unstemmed | The Laplace Likelihood Ratio Test for Heteroscedasticity |
| title_short | The Laplace Likelihood Ratio Test for Heteroscedasticity |
| title_sort | laplace likelihood ratio test for heteroscedasticity |
| url | http://dx.doi.org/10.1155/2011/249564 |
| work_keys_str_mv | AT jmartinvanzyl thelaplacelikelihoodratiotestforheteroscedasticity AT jmartinvanzyl laplacelikelihoodratiotestforheteroscedasticity |