Title :

Interpolation and linear prediction of data -three kernel selection criteria

Author(s) :

Dermoune, Azzouz [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Sebaiy, Mohammed [Auteur]
Moustaaid, Jabrane [Auteur]

Publication date :

2021-07-05

English keyword(s) :

Kernel interpolation stochastic interpolation linear algebra interpolation cubic spline interpolation climate change detection
Kernel interpolation
stochastic interpolation
linear algebra interpolation
cubic spline interpolation
climate change detection

HAL domain(s) :

Mathématiques [math]

English abstract : [en]

Interpolation and prediction have been useful approaches in modeling data in many areas of applications. The aim of this paper is the prediction of the next value of a time series (time series forecasting) using the ...
Show more >Interpolation and prediction have been useful approaches in modeling data in many areas of applications. The aim of this paper is the prediction of the next value of a time series (time series forecasting) using the techniques in interpolation of the spatial data, for the two approaches kernel interpolation and kriging. We are interested in finding some sufficient conditions for the kernels and provide a detailed analyse of the prediction using kernel interpolation. Finally, we provide a natural idea to select a good kernel among a given family of kernels using only the data. We illustrate our results by application to the data set on the mean annual temperature of France and Morocco recorded for a period of 115 years (1901 to 2015).Show less >

Language :

Anglais

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL

Submission date :

2025-01-24T13:57:27Z