Statistical analysis and forecasting of meteorological data
This article synthesizes data on the daily average air temperature for December from the Tashkent-
Observatory meteorological station over the years 1904–2023 (120 years of observations), and
analyzes these data using statistical methods to explore forecasting possibilities. The paper details
preliminary examinations of the time series (exploratory analysis; decomposition of trend and
seasonality using STL), tests for stationarity (ADF and KPSS), identification of the correlation
structure (via ACF and PACF), and the selection, parameter estimation, diagnostics, and assessment
(both as model diagnostics and forecasts) of classical models including AR, MA, ARMA, ARIMA,
and SARIMA.
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