Sensitivity analysis of error-contaminated time series data under autoregressive models with the application of COVID-19 data
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Publication:6134407
DOI10.1080/02664763.2022.2034760arXiv2008.05649MaRDI QIDQ6134407
Publication date: 25 July 2023
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2008.05649
Cites Work
- Statistical analysis with measurement error or misclassification. Strategy, method and application
- Prediction and forecasting in linear models with measurement error
- Estimation of models of autoregressive signal plus white noise
- Theoretical comparisons of block bootstrap methods
- Asymptotic properties of estimators for autoregressive models with errors in variables
- Regression and time series model selection in small samples
- Introduction to Time Series and Forecasting
- A UNIFIED APPROACH TO THE MEASUREMENT ERROR PROBLEM IN TIME SERIES MODELS
- Estimation in autoregressive model with measurement error
- Measurement Error in Linear Autoregressive Models
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