## Electronic Communications in Probability

### Optimising prediction error among completely monotone covariance sequences

Ross McVinish

#### Abstract

We provide a characterisation of Gaussian time series which optimise the one-step prediction error subject to the covariance sequence being completely monotone with the first $m$ covariances specified.

#### Article information

Source
Electron. Commun. Probab., Volume 13 (2008), paper no. 11, 113-120.

Dates
Accepted: 2 March 2008
First available in Project Euclid: 6 June 2016

https://projecteuclid.org/euclid.ecp/1465233438

Digital Object Identifier
doi:10.1214/ECP.v13-1355

Mathematical Reviews number (MathSciNet)
MR2386067

Zentralblatt MATH identifier
1191.60049

Subjects
Secondary: 44A60: Moment problems

Rights

#### Citation

McVinish, Ross. Optimising prediction error among completely monotone covariance sequences. Electron. Commun. Probab. 13 (2008), paper no. 11, 113--120. doi:10.1214/ECP.v13-1355. https://projecteuclid.org/euclid.ecp/1465233438

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