Hello and good evening,
I am not completely sure, if this is bug, but I did not find any relevant answer.
I run DAPC on MSATs data and morphological data predominantely. However, in most cases I get DAPC with 98 - 99.9 % of variance explained by Axis 1. I tried several data transformation, scaling, centering, bur result is still the same. Results make sense from biological point of view, but I am worried, if there is any problem I might miss.
Is this case of overfitting? Or linearity of data? Or might this be result of some problem in my script?
I use mostly a bit edited script by Tom Jenkins:
https://tomjenkins.netlify.app/.../r-popgen-getting-started/
Hello and good evening, I am not completely sure, if this is bug, but I did not find any relevant answer. I run DAPC on MSATs data and morphological data predominantely. However, in most cases I get DAPC with 98 - 99.9 % of variance explained by Axis 1. I tried several data transformation, scaling, centering, bur result is still the same. Results make sense from biological point of view, but I am worried, if there is any problem I might miss. Is this case of overfitting? Or linearity of data? Or might this be result of some problem in my script? I use mostly a bit edited script by Tom Jenkins: https://tomjenkins.netlify.app/.../r-popgen-getting-started/
Thanks in advance for any help.