W.-K. Wong and G. R. Bian, “Estimating Parameters in Autoregressive Models with Asymmetric Innovations,” Statistics and Probability Letters, Vol. 71, No. 1, 2005, pp. 61-70. - References

Browse Menu >>

Browse Subjects >>

Computer Science & Communications

Earth & Environmental Sciences

Social Sciences & Humanities

Why Us? >>

- Open Access
- Peer-reviewed
- Rapid publication
- Lifetime hosting
- Free indexing service
- Free promotion service
- More citations
- Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

Contact Us >>

customer@scirp.org

+86 18163351462(WhatsApp)

1655362766

Paper Publishing WeChat

Book Publishing WeChat

(or Email:book@scirp.org)

Article citations
More>>

W.-K. Wong and G. R. Bian, “Estimating Parameters in Autoregressive Models with Asymmetric Innovations,” Statistics and Probability Letters, Vol. 71, No. 1, 2005, pp. 61-70.
http://dx.doi.org/10.1016/j.spl.2004.10.022

has been cited by the following article:

TITLE: Estimation of a Type of Form-Invariant Combined Signals under Autoregressive Operators

AUTHORS: Yinsheng Zhang, Jing Yao, Dongyun Yi

KEYWORDS: Form-Invariant Signals; Autoregressive Operator; Autoregressive Noise; Parameter Estimation

JOURNAL NAME: Open Journal of Statistics, Vol.3 No.6, December 31, 2013

ABSTRACT: We focus on a type of combined signals whose forms remain invariant under the autoregressive operators. To extract the true signal from the autoregressive noise, we develop a strategy to separate parameters and use a two-step least squares approach to estimate the autoregressive parameters directly and then further give the estimate of the signal parameters. This method overcomes the difficulty that the autoregressive noise remains unknown in other methods. It can effectively separate the noise and extract the true signal. The algorithm is linear. The solution of the problem is computationally cheap and practical with high accuracy.