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A Note on the Asymptotic Normality of Sample Autocorrelations for a Linear Stationary Sequence
- Source :
- Journal of Multivariate Analysis. (2):182-188
- Publisher :
- Academic Press.
-
Abstract
- We consider a stationary time series {Xt} given byXt=∑∞k=−∞ψkZt−k, where {Zt} is a strictly stationary martingale difference white noise. Under assumptions that the spectral densityf(λ) of {Xt} is squared integrable andmτ∑|k|⩾mψ2k→0 for someτ>1/2, the asymptotic normality of the sample autocorrelations is shown. For a stationary long memoryARIMA(p, d, q) sequence, the conditionmτ∑|k|⩾mψ2k→0 for someτ>1/2 is equivalent to the squared integrability off(λ). This result extends Theorem 4.2 of Cavazos-Cadena [5], which were derived under the conditionm∑|k|⩾mψ2k→0.
- Subjects :
- Statistics and Probability
Numerical Analysis
Autocorrelation
autocorrelation
central limit theorem
Asymptotic distribution
Spectral density
White noise
Stationary sequence
Combinatorics
martingale difference
Calculus
Martingale difference sequence
Statistics, Probability and Uncertainty
Martingale (probability theory)
ARIMA model
Mathematics
Central limit theorem
Subjects
Details
- Language :
- English
- ISSN :
- 0047259X
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Journal of Multivariate Analysis
- Accession number :
- edsair.doi.dedup.....a11f29a00cc60f05392dc8d4df6f55e6
- Full Text :
- https://doi.org/10.1006/jmva.1996.0046