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

Zhang, Qihuang; Yi, Grace Y

Zhang, Qihuang; Yi, Grace Y.

Afiliação

Zhang Q; Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada.
Yi GY; Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada.

J Appl Stat ; 50(7): 1611-1634, 2023.

Article em En | MEDLINE | ID: mdl-37197758

Palavras-chave

Autoregressive model; COVID-19; forecasting; measurement error; sensitivity analysis; time series

Texto completo

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184652
https://dx.doi.org/10.1080/02664763.2022.2034760

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184652
https://dx.doi.org/10.1080/02664763.2022.2034760

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article