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Modeling and forecasting of metrological factors using arch process under different errors distribution specification

Mishra, Pradeep ; Fatih, Chellai ; Vani, G. K. ; Lavrod, Jakob Mattias ; Mishra, P. C. ; Choudhary, Arun Kumar ; Jain, Vikas and Dubey, Anurag (2021) In Mausam 72(2). p.301-312
Abstract

Various weather phenomenon are difficult to model and forecast with high precision. This study has modelled and forecasted the various parameter namely maximum and minimum temperature, morning and evening relative humidity using parametric models namely Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive conditional heteroskedasticity (GARCH)) models. The data consisted of daily time series data for Hoshangabad district of Madhya Pradesh from January, 1996 to November, 2019. The AIC and BIC criterion were used to select among competing models. Present investigation has revealed that ARIMA-GARCH models are more suitable for forecasting of minimum temperature, maximum temperature and relative humidity.

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author
; ; ; ; ; ; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
ARCH, Error distribution, GARCH, Time series, Weather
in
Mausam
volume
72
issue
2
pages
12 pages
publisher
India Meteorological Department
external identifiers
  • scopus:85107947634
ISSN
0252-9416
language
English
LU publication?
no
id
6ee181fe-fca5-4584-ad31-854f062d4a90
date added to LUP
2021-07-14 14:36:45
date last changed
2022-04-27 02:47:33
@article{6ee181fe-fca5-4584-ad31-854f062d4a90,
  abstract     = {{<p>Various weather phenomenon are difficult to model and forecast with high precision. This study has modelled and forecasted the various parameter namely maximum and minimum temperature, morning and evening relative humidity using parametric models namely Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive conditional heteroskedasticity (GARCH)) models. The data consisted of daily time series data for Hoshangabad district of Madhya Pradesh from January, 1996 to November, 2019. The AIC and BIC criterion were used to select among competing models. Present investigation has revealed that ARIMA-GARCH models are more suitable for forecasting of minimum temperature, maximum temperature and relative humidity.</p>}},
  author       = {{Mishra, Pradeep and Fatih, Chellai and Vani, G. K. and Lavrod, Jakob Mattias and Mishra, P. C. and Choudhary, Arun Kumar and Jain, Vikas and Dubey, Anurag}},
  issn         = {{0252-9416}},
  keywords     = {{ARCH; Error distribution; GARCH; Time series; Weather}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{301--312}},
  publisher    = {{India Meteorological Department}},
  series       = {{Mausam}},
  title        = {{Modeling and forecasting of metrological factors using arch process under different errors distribution specification}},
  volume       = {{72}},
  year         = {{2021}},
}