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Article: SIGNIFICANT VARIABLE SELECTION AND AUTOREGRESSIVE ORDER DETERMINATION FOR TIME-SERIES PARTIALLY LINEAR MODELS
Title | SIGNIFICANT VARIABLE SELECTION AND AUTOREGRESSIVE ORDER DETERMINATION FOR TIME-SERIES PARTIALLY LINEAR MODELS |
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Authors | |
Issue Date | 2014 |
Publisher | Wiley. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9892 |
Citation | Journal of Time Series Analysis, 2014, v. 35, p. 478-490 How to Cite? |
Abstract | This paper is concerned with the regression coefficient and autoregressive order shrinkage and selection via the smoothly clipped absolute deviation (SCAD) penalty for a partially linear model with time-series errors. By combining the profile semi-parametric least squares method and SCAD penalty technique, a new penalized estimation for the regression and autoregressive parameters in the model is proposed. We show that the asymptotic property of the resultant estimator is the same as if the order of autoregressive error structure and non-zero regression coefficients are known in advance, thus achieving the oracle property in the sense of Fan and Li (2001). In addition, based on a prewhitening technique, we construct a two-stage local linear estimator (TSLLE) for the non-parametric component. It is shown that the TSLLE is more asymtotically efficient than the one that ignores the autoregressive time-series error structure. Some simulation studies are conducted to illustrate the finite sample performance of the proposed procedure. An example of application on electricity usage data is also illustrated. |
Persistent Identifier | http://hdl.handle.net/10722/209823 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, D | en_US |
dc.contributor.author | Li, G | en_US |
dc.contributor.author | You, J | en_US |
dc.date.accessioned | 2015-05-18T03:26:30Z | - |
dc.date.available | 2015-05-18T03:26:30Z | - |
dc.date.issued | 2014 | en_US |
dc.identifier.citation | Journal of Time Series Analysis, 2014, v. 35, p. 478-490 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/209823 | - |
dc.description.abstract | This paper is concerned with the regression coefficient and autoregressive order shrinkage and selection via the smoothly clipped absolute deviation (SCAD) penalty for a partially linear model with time-series errors. By combining the profile semi-parametric least squares method and SCAD penalty technique, a new penalized estimation for the regression and autoregressive parameters in the model is proposed. We show that the asymptotic property of the resultant estimator is the same as if the order of autoregressive error structure and non-zero regression coefficients are known in advance, thus achieving the oracle property in the sense of Fan and Li (2001). In addition, based on a prewhitening technique, we construct a two-stage local linear estimator (TSLLE) for the non-parametric component. It is shown that the TSLLE is more asymtotically efficient than the one that ignores the autoregressive time-series error structure. Some simulation studies are conducted to illustrate the finite sample performance of the proposed procedure. An example of application on electricity usage data is also illustrated. | en_US |
dc.language | eng | en_US |
dc.publisher | Wiley. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-9892 | - |
dc.relation.ispartof | Journal of Time Series Analysis | en_US |
dc.rights | This is the accepted version of the following article: Journal of Time Series Analysis, 2014, v. 35, p. 478-490 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/jtsa.12077/abstract | - |
dc.title | SIGNIFICANT VARIABLE SELECTION AND AUTOREGRESSIVE ORDER DETERMINATION FOR TIME-SERIES PARTIALLY LINEAR MODELS | en_US |
dc.type | Article | en_US |
dc.identifier.email | Li, G: gdli@hku.hk | en_US |
dc.identifier.authority | Li, G=rp00738 | en_US |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1111/jtsa.12077 | en_US |
dc.identifier.hkuros | 243285 | en_US |
dc.identifier.volume | 35 | en_US |
dc.identifier.spage | 478 | en_US |
dc.identifier.epage | 490 | en_US |
dc.identifier.isi | WOS:000341240100006 | - |
dc.publisher.place | United Kingdom | - |