Data Driven IFS

Not all data are written in an alphabet of four symbols. Can we adapt the driven IFS method to study a wider variety of data, daily closing stock prices, for example? The answer is yes. As a first step, we must coarse-grain the data.

First, here are some examples using mathematical data. From these we can gain familiarity with some of the visual signatures of different time patterns in the data.

Here are some examples of student projects using financial data.

Here are some examples of student projects using texts.

Finally, here we interpret some of these examples to try to estimate the "depth of history" of the underlying processes.

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