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Stationary Gaussian Markov processes as limits of stationary autoregressive time series

Publication ,  Journal Article
Ernst, PA; Brown, LD; Shepp, L; Wolpert, RL
Published in: Journal of Multivariate Analysis
March 1, 2017

We consider the class, Cp, of all zero mean stationary Gaussian processes, {Yt:t∈(−∞,∞)} with p derivatives, for which the vector valued process {(Yt(0),…,Yt(p)):t≥0} is a p+1-vector Markov process, where Yt(0)=Y(t). We provide a rigorous description and treatment of these stationary Gaussian processes as limits of stationary AR(p) time series.

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Published In

Journal of Multivariate Analysis

DOI

EISSN

1095-7243

ISSN

0047-259X

Publication Date

March 1, 2017

Volume

155

Start / End Page

180 / 186

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 3802 Econometrics
  • 1403 Econometrics
  • 0104 Statistics
 

Citation

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Ernst, P. A., Brown, L. D., Shepp, L., & Wolpert, R. L. (2017). Stationary Gaussian Markov processes as limits of stationary autoregressive time series. Journal of Multivariate Analysis, 155, 180–186. https://doi.org/10.1016/j.jmva.2016.12.008
Ernst, P. A., L. D. Brown, L. Shepp, and R. L. Wolpert. “Stationary Gaussian Markov processes as limits of stationary autoregressive time series.” Journal of Multivariate Analysis 155 (March 1, 2017): 180–86. https://doi.org/10.1016/j.jmva.2016.12.008.
Ernst PA, Brown LD, Shepp L, Wolpert RL. Stationary Gaussian Markov processes as limits of stationary autoregressive time series. Journal of Multivariate Analysis. 2017 Mar 1;155:180–6.
Ernst, P. A., et al. “Stationary Gaussian Markov processes as limits of stationary autoregressive time series.” Journal of Multivariate Analysis, vol. 155, Mar. 2017, pp. 180–86. Scopus, doi:10.1016/j.jmva.2016.12.008.
Ernst PA, Brown LD, Shepp L, Wolpert RL. Stationary Gaussian Markov processes as limits of stationary autoregressive time series. Journal of Multivariate Analysis. 2017 Mar 1;155:180–186.
Journal cover image

Published In

Journal of Multivariate Analysis

DOI

EISSN

1095-7243

ISSN

0047-259X

Publication Date

March 1, 2017

Volume

155

Start / End Page

180 / 186

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 3802 Econometrics
  • 1403 Econometrics
  • 0104 Statistics