can we implement PCA for lets 10 subjects 3 repeated trials with each trial 101 samples and variable vertical-GRF i.e. 101*30 input matrix

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imran mahmood 2018-9-17

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评论： Kartik Mittal 2018-9-28

Principal Component Analysis

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Kartik Mittal 2018-9-25

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My understanding of the problem is that you have 101 data points, each with 30 attributes? If that is the case, you can use PCA. But I am not sure you have a correct feature vector for what you are calling the data points (samples). If you have 10 subjects, with 3 trials, how are they attributive of one sample? In your case PCA would make sense if there is some correlation between trials, like stages of an experiment or something.

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imran mahmood 2018-9-27

Sample Data.xlsx

Hi Kartik thanks again, I am attaching the data set for my further understanding. In this data ankle-joint angle is measured as time-series waveforms. Three trials/waveforms were measured from each subject. There were total 10 subjects. I want to minimise the variance between the waveforms over the time span (101 samples). Can I use PCA?

Kartik Mittal 2018-9-28

Thanks for the information, it makes the case clear that you will have repeated measures as your data points (given all the trials are with one experimental condition). Hence, PCA would not be an obvious choice for what you wish to do. Check this link - https://stats.stackexchange.com/questions/18617/can-i-do-a-pca-on-repeated-measures-for-data-reduction

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