Cited by 1,039Time Series Analysis and ForecastingStatistical and numerical algorithmsStatistical Methods and Applications

Time Series Analysis and Its Applications

Shumway, Robert H., Stoffer, David S.·2000·Springer Texts in Statistics

Integrity signals

Registry

Crossref · 10.1007/978-1-4757-3261-0

Cites

Statistics

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Claims the paper makes

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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The Kalman filter can give the minimum mean-squared error within the class of linear estimators even if the noise assumption does not hold.

    “Even if the assumption of the noise does not hold, it was shown that the Kalman filter [33] can give the minimum mean-squared error within the class of linear estimators.”

Cited by

Sorted by citations

Authors
Shumway, R. H., & Stoffer, D. S.
Affiliations
University of Pittsburgh (US)
Venue
Springer Texts in Statistics
Published
2000
ISSN
1431-875X (ISSN-L)
OpenAlex
W4210616753
Cited by
1,039
References
0
Citations by year
2026: 43 · 2025: 119 · 2024: 90 · 2023: 67 · 2022: 50 · 2021: 27 · 2020: 24 · 2019: 17 · 2018: 29 · 2017: 25 · 2016: 31 · 2015: 23 · 2014: 38 · 2013: 39 · 2012: 31
FWCI
10.96
Type
book
Language
en
Open access
closed
Locations
  • Springer texts in statistics (publishedVersion)
  • CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Signal Processing › Time Series Analysis and Forecasting
  • Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords
time series analysis, time series modeling, forecasting, autocorrelation, stationarity, ARIMA model

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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