Hi,
I am trying to reduce numbers of explanatory variables in my analysis. I
have 9 nominal independent variables, seven are binomials and two have
more levels. I had planned use PCA (prcomp {stats}) but I have some
factors with more of two levels. Thus, I am using a Multiple
Correspondence Analysis (MCA {FactoMineR}) and Homogeneity Analysis
(homals {homals packages}) to compare results.
My problem is that I can't find, for MCA and homals objects, a function
similar to "predict {stats}", which is used on prcomp objects and
generate axis values for each individual (species in my case).
Thanks in advance!
Diego Salazar
--
Diego Francisco Salazar Tortosa
Ph student
Departamento de Ecología
Facultad de Ciencias
Universidad de Granada
Av. Fuente Nueva s/n
18071 Granada
Telefono: +34 958241000 ext 20007
Movil: +34 634851132
email: dsala...@ugr.es
dftort...@gmail.com
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