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  • 标题:A New Heteroskedastic Consistent Covariance Matrix Estimator using Deviance Measure
  • 本地全文:下载
  • 作者:Nuzhat Aftab ; Sohail Chand
  • 期刊名称:Pakistan Journal of Statistics and Operation Research
  • 印刷版ISSN:2220-5810
  • 出版年度:2016
  • 卷号:12
  • 期号:2
  • 页码:235-244
  • DOI:10.18187/pjsor.v12i2.983
  • 语种:English
  • 出版社:College of Statistical and Actuarial Sciences
  • 摘要:In this article we propose a new heteroskedastic consistent covariance matrix estimator, HC6, based on deviance measure. We have studied and compared the finite sample behavior of the new test and compared it with other this kind of estimators, HC1, HC3 and HC4m, which are used in case of leverage observations. Simulation study is conducted to study the effect of various levels of heteroskedasticity on the size and power of quasi-t test with HC estimators. Results show that the test statistic based on our new suggested estimator has better asymptotic approximation and less size distortion as compared to other estimators for small sample sizes when high level of heteroskedasticity is present in data.
  • 其他摘要:In this article we propose a new heteroskedastic consistent covariance matrix estimator, HC6, based on deviance measure. We have studied and compared the finite sample behavior of the new test and compared it with other this kind of estimators, HC1, HC3 and HC4m, which are used in case of leverage observations. Simulation study is conducted to study the effect of various levels of heteroskedasticity on the size and power of quasi-t test with HC estimators. Results show that the test statistic based on our new suggested estimator has better asymptotic approximation and less size distortion as compared to other estimators for small sample sizes when high level of heteroskedasticity is present in data.
  • 关键词:Heteroscedasticity; Covariance Matrix; Deviance
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