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 tow 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).

翻译：内插和预测是在许多应用领域建立数据模型的有用方法,本文件的目的是利用空间数据内插技术预测时间序列(时间序列预测)的下一个数值,用于牵引途径内插和轮刺,我们有兴趣为内核找到一些足够的条件,并详细分析利用内核内插的预测情况,最后,我们提供了一种自然的想法,只利用数据在特定内核组别中选择一个好的内核,我们通过对记录了115年(1901年至2015年)法国和摩洛哥平均年温数据集的应用来说明我们的结果。