vbonhomme
commented
1 year ago Ideally yes. So far no. But soon, say this autumn, yes !
Le dim. 10 juil. 2022 à 19:40, theropod1 @.***> a écrit :
Hi! Love your package!
I have a question/perhaps a feature request:
Namely, I’m working on visualization of PCA morphospaces using the PCcontrib() function.
For example: PCcontrib(my_pca_object, nax=1:1, sd.r=c(-1))
I understand this will return me the shape at -1 standard deviation on PC1, and at 0 for all the other PCs.
What I am wondering is if there is a way to also visualize shapes that are at some arbitrary point in shape space, e.g. at -1 on PC1 and -1 on PC2. Package Geomorph does something similar with its shape.predictor(), which allows to predict the shape for any combination of predictor variables (i.e. PC values). Is there a way to accomplish something like this in Momocs? Additionally
Many thanks!
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Hi! Love your package!
I have a question/perhaps a feature request:
Namely, I’m working on visualization of PCA morphospaces using the PCcontrib() function.
For example: PCcontrib(my_pca_object, nax=1:1, sd.r=c(-1))
I understand this will return me the shape at -1 standard deviation on PC1, and at 0 for all the other PCs.
What I am wondering is if there is a way to also visualize shapes that are at some arbitrary point in shape space, e.g. at -1 on PC1 and -1 on PC2. Package Geomorph does something similar with its shape.predictor(), which allows to predict the shape for any combination of predictor variables (i.e. PC values). Is there a way to accomplish something like this in Momocs?
Many thanks!