Adaptive Estimation of Autoregressive Models with Time-Varying Variances
Stable autoregressive models are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change ove...
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| المؤلفون الرئيسيون: | , |
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| التنسيق: | text |
| اللغة: | English |
| منشور في: |
Institutional Knowledge at Singapore Management University
2008
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/soe_research/288 https://ink.library.smu.edu.sg/context/soe_research/article/1287/viewcontent/Adaptive_Estimation_of_Autoregressive_Models_2008.pdf |
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| المؤسسة: | Singapore Management University |
| اللغة: | English |
| الملخص: | Stable autoregressive models are considered with martingale differences errors scaled by an unknown nonparametric time-varying function generating heterogeneity. An important special case involves structural change in the error variance, but in most practical cases the pattern of variance change over time is unknown and may involve shifts at unknown discrete points in time, continuous evolution or combinations of the two. This paper develops kernel-based estimators of the residual variances and associated adaptive least squares (ALS) estimators of the autoregressive coefficients. Simulations show that efficiency gains are achieved by the adaptive procedure. |
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