Hi all! I am a newcomer in the field of GM and have recently applied several GM tools for describing a new form across its developmental processes and analyzing the impact of infections on shape. For 8 successive days, I analyzed with MorphoJ (PCAs, DAs, etc) the change in shape that was induced by the treatment, versus the control group.
When sended the paper for revision, one Reviewer asked: "Are there any reasons why PCA analysis limitations (use of variance, linear projection) should not considered important in this analysis ? This kind of question should be addressed, because they are at the heart of any interesting question anyone would ask in performing such analysis : the relations between morphogenesis and variance. It seems unclear to me, after having read the article, why kernel PCA should not be privileged versus PCA. <#_msocom_1>" What is kernel PCA? Is it of standard use in GM? If not, what do you think the best answer should be? (I used PCAs only to show differences between individuals and only relied on DAs for stating group differences at each one of the 8 successive days analyzed). Thanks a lot! -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org --- You received this message because you are subscribed to the Google Groups "MORPHMET" group. To unsubscribe from this group and stop receiving emails from it, send an email to morphmet+unsubscr...@morphometrics.org.