Sensitivity analysis of error-contaminated time series data under autoregressive models with the application of COVID-19 data-Reference-Cited by-同舟云学术

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Sensitivity analysis of error-contaminated time series data under autoregressive models with the application of COVID-19 data

Published:2022-02-16 Issue: Volume: Page:1-24
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Zhang Qihuang¹^ORCID,Yi Grace Y.¹²³^ORCID

Affiliation:

1. Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada

2. Department of Statistical and Actuarial Sciences, University of Western Ontario, London, Ontario, Canada

3. Department of Computer Science, University of Western Ontario, London, Ontario, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Canadian Network for Research and Innovation in Machining Technology

Canada Research Chairs in Sexual and Gender Minority Health

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2022.2034760

Reference21 articles.

1. Real estimates of mortality following COVID-19 infection

2. Introduction to Time Series and Forecasting

3. Asymptotic properties of estimators for autoregressive models with errors in variables

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Time series forecasting of the COVID-19 pandemic: a critical assessment in retrospect;Alphanumeric Journal;2023-07-12

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