Modelling time series with data mining

Some of the models obtained in the study of time series using data mining in the group of Málaga are presented. Firstly, two methods to assign discrete values to continuous values from time series are proposed; these methods use dynamic information about the series. The first method is based on a particular statistic which allows us to select a discrete value for a new continuous value from the series. The second one is based on the proposed concept of significant distance between consecutive values from time series. Secondly, the use of probabilistic finite automata to model time series are described. Finally, an algorithm to generate time series with the same statistical properties that the real ones is presented.