Skip to main content
Cross Validated

You are not logged in. Your edit will be placed in a queue until it is peer reviewed.

We welcome edits that make the post easier to understand and more valuable for readers. Because community members review edits, please try to make the post substantially better than how you found it, for example, by fixing grammar or adding additional resources and hyperlinks.

6
  • $\begingroup$ I Have wrote a paper and i have only used (the combinition between PCA and wavelet analysis), the reviewer recommend to use some others approches and compare them with my method, i have sequence of profiles (taken for each unit of time) and each profile contains 1000 variables , also my profiles are nonlinear $\endgroup$ Commented Jul 20, 2012 at 22:53
  • $\begingroup$ i have used wavelet analysis (the reduce noise and compress data) after that PCA, it should be noted that if we take a look in the profile (at time t), the profile is approximately linear, but if we look to the variable nonlinear, i am interested to select some significant few variables $\endgroup$ Commented Jul 20, 2012 at 22:59
  • $\begingroup$ So the problem is just to find reduced-dimensional representation of n nonlinear profiles consisting of 1000 variables? And n << 1000? $\endgroup$ Commented Jul 21, 2012 at 5:18
  • $\begingroup$ yes, the number of profiles is lower than the number of variables. and i want to retain only few significant variables and drawn each one of them vs (times= n profiles) $\endgroup$ Commented Jul 21, 2012 at 7:20
  • $\begingroup$ could you please provide an example plot of profile (if it is applicable) or actual data? And what is your final goal? $\endgroup$ Commented Jul 21, 2012 at 7:32