Real Time Monitoring of Carbon Monoxide Using Value-at-Risk Measure and Control Charting
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- Sotirios Bersimis & Stavros Degiannakis & Dimitrios Georgakellos, 2017. "Real-time monitoring of carbon monoxide using value-at-risk measure and control charting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 89-108, January.
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- Mustapha Rachdi & Ali Laksaci & Noriah M. Al-Kandari, 2022. "Expectile regression for spatial functional data analysis (sFDA)," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(5), pages 627-655, July.
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More about this item
Keywords
Air Quality Surveillance; Atmospheric Pollution; Autoregressive Conditional Heteroskedasticity modelling; Control Charts; Diag-aVECH; Multivariate Statistical Process Monitoring; Multivariate Time Series; Value-at-Risk.;All these keywords.
JEL classification:
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ENE-2016-03-29 (Energy Economics)
- NEP-ENV-2016-03-29 (Environmental Economics)
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