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

6 Ansichten (letzte 30 Tage)
Principal Component Analysis

Antworten (1)

Kartik Mittal
Kartik Mittal am 25 Sep. 2018
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.
  4 Kommentare
imran mahmood
imran mahmood am 27 Sep. 2018
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
Kartik Mittal am 28 Sep. 2018
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

Melden Sie sich an, um zu kommentieren.

Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by