Pattern recognition in time series

[#1]

I have found how clustering techniques can be used in JMP to identify similar patterns:

https://community.jmp.com/t5/Discussions/How-to-determine-clusters-of-semiconductor-wafer-defect-sor...

When analyzing time series data I am often interested in clustering periods where a pattern of interest appears. In the literature there are several techniques and I wonder how JMP/JMP Pro can be used to have some initial results.

[#2]

Can you share the specific instances/techniques in the literature that you are interested in using? Then compared capabilties in JMP/JMP Pro wrt to these specific instances?

[#3]

This answer from quora is a good summary of different techniques that can be used previous clustering.

src: quora.com/What-is-the-best-way-algorithm-to-detect-a-pattern-in-a-time-series

• Cross correlation 
• Windowed dynamic time warping
• Fingerpinting the time series using a combination of statistics
• Hidden Markov Models
• Recurrent Neural Networks 

[#4 · Accepted solution]

I think the Functional Data Explorer platform may help you here. You can save functional principal components for each time series and then cluster based on those principal components.

Here are some tutorials on the Functional Data Explorer:

[#5]

Interesting approach -  one can take advantage of the data preprocessing and dynamic time warping within the FDE platform.

[#6]

In addition to the Functional Data Explorer platform (only available in JMP Pro) you may also want to check out the Time Series platform in JMP (which is also in JMP Pro since JMP capabilities are a subset of JMP Pro capabilties). There are many pattern recognition subplatforms/visualization options nested within the platform. As one of the quora respondents so wisely stated, '...it depends on the pattern your're looking for.' Here's a link to the JMP online documentation for the Time Series platform:

https://www.jmp.com/support/help/14-2/time-series-analysis.shtml#