I have a collection of time series data. The data is structured (Country, Year, Value).
~50 countries and ~30 data points for each country
Is there a way to cluster time series? Time intervals are uniform and measuring the same output across different countries (0 < value < 1).
Plotting the values at a glance, it looks like there are two obvious groups of countries.
I have seen people mention fitting an ARIMA or a polynomial regression model to the data. And then compare the co-efficients to cluster them. (chow test). But i have also read that the chow test, tests for the presence of a structural break at a period. Is this a sound approach?
I am only interested in grouping by countries that have the most similar time series (what measure of similarity?) together into 2-4 clusters.
Also I should have noted that the number of data points for each series can vary.