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Cited by 492

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

LEAST SQUARES ESTIMATION OF A SHIFT IN LINEAR PROCESSES

Bai, Jushan·1994·Journal of Time Series Analysis

Abstract

Abstract. This paper considers a mean shift with an unknown shift point in a linear process and estimates the unknown shift point (change point) by the method of least squares. Pre‐shift and post‐shift means are estimated concurrently with the change point. The consistency and the rate of convergence for the estimated change point are established. The asymptotic distribution for the change point estimator is obtained when the magnitude of shift is small. It is shown that serial correlation affects the variance of the change point estimator via the sum of the coefficients of the linear process. When the underlying process is autoregressive moving average, a mean shift causes overestimation of its order. A simple procedure is suggested to mitigate the bias in order estimation.

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Crossref · 10.1111/j.1467-9892.1994.tb00204.x

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Metadata

Authors
Bai, J.
Venue
Journal of Time Series Analysis
Publisher
Wiley
Published
1994-09
Volume
15
Issue
5
Pages
453-472
ISSN
  • 0143-9782 (ISSN-L)
  • 1467-9892
OpenAlex
W1587806953
Cited by
492
References
2
FWCI
5.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: LEAST SQUARES ESTIMATION OF A SHIFT IN LINEAR PROCESSES. https://app.cochat.ai/papers/10.1111/j.1467-9892.1994.tb00204.x
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Bai, J. (1994). LEAST SQUARES ESTIMATION OF A SHIFT IN LINEAR PROCESSES. Journal of Time Series Analysis. https://doi.org/10.1111/j.1467-9892.1994.tb00204.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.