Influence of Missing Values on the Prediction of a Stationary Time Series

Influence of Missing Values on the Prediction of a Stationary Time Series

.  The influence of missing observations on the linear prediction of a stationary time series is investigated. Simple bounds for the prediction error variance and asymptotic behaviours for short and long‐memory processes respectively are presented.

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Veröffentlicht in:Journal of time series analysis 2005-07, Vol.26 (4), p.519-525
1. Verfasser: Bondon, Pascal
Format: Artikel
Sprache:eng
Schlagworte:
asymptotic behaviour
long-memory
Mathematical models
missing value problems
Prediction theory
Primary 62M10
secondary 60G25
Studies
Time series
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Beschreibung
Zusammenfassung:.  The influence of missing observations on the linear prediction of a stationary time series is investigated. Simple bounds for the prediction error variance and asymptotic behaviours for short and long‐memory processes respectively are presented.
ISSN:0143-9782
1467-9892
DOI:10.1111/j.1467-9892.2005.00433.x