FAMD

[Pau Lucio]

Dear Francois and FactormineR users,

Lovely package with good tutorials.

I am working on a FAMD analysis where I have 22 variables (18 numerical, i.e., different land use, rainfall, etc. and 4 categorical variables, i.e., dominant land use, dominant vegetation cover, etc). My aim is to see which variables have a stronger effect to a particular bird species. So, to archive this we did 71-point counts which were repeated 23 times along 13 months. So, in total we have roughly 1600 surveys (n rows), which have bird values from 0 birds to 24, but in most of the surveys we recorded 0 birds. I would like to plot the bird observation and see their distribution with the variables. Should I only choose the rows where we count 1 or more birds and not to choose the 0’s? How could I incorporate the bird column counts in the formula?

I tried this:

res.famd <- FAMD(FAMD.data, graph = FALSE, ind.sup = 1)

FAMD.data are 22 variables

Ind.sup = 1 columns from the surwey

Please, could you advise?

 

Many thanks

[E M]

Hi,

I don’t really have an answer to your question. However, I urge you to try using the factoshiny package. It’s a great place to start using FAMD, and other similar packages to manipulate your data. It almost works like a computer web browser extension where you don’t have to put in the majority of the work coding/get free code without doing a lot of the labor. You can just plug in your data set and go. It was a great start to figure out the bounds of my data set and to see what variables to set as the main characters (0 or 1s).

Context: My thesis, I used FAMD. I had missing variables (missmda package). Overall I was looking at morphological components of 12 plant species for over 30 variable comparisons. 

Again, strongly urge you to play around with factoshiny if you haven’t already. If you have, I apologize for a reflective email! 

Best,

A fellow scientist. 

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