Abstract

MENESES FREIRE, Antonio et al. Non parametric functional predictive model in functional time series. Application in meteorological variables. Perfiles [online]. 2022, vol.1, n.28, pp.83-89. ISSN 2477-9105.  https://doi.org/10.47187/perf.v1i28.186.

20.

The research starts from the study of the non-parametric functional model for functional time series. The objective is to establish predictions of functional time series that are formed with the sample of the average wind speeds in each hour of the months of January to December of the year 2019. The sample was taken from the meteorological station of the Escuela Superior Politécnica de Chimborazo located in the San Juan Parish at 4350 meters above sea level at the 30th kilometer of the Calpi - Guaranda road in the province of Chimborazo- Ecuador. The fda,usc package of the R software was used for the application of the functional time series in the aforementioned model, then with this model the adjustments were obtained, the optimal window width typical of a non-parametric model, the predictions of the Time series of 24 values corresponding to each hour in the interval from 0:00 to 23:00, very close to the series of wind speeds for the month of December taken as the control month. This sets the standard to testify that the adjusted model in this research is significantly reliable, and opens the way for future applications in other meteorological variables.

Keywords : Functional nonparametric model; functional time series; meteorological variables; wind speed.

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