Dear community,
First of all, apologies, I'm pretty newbie, and maybe have not truly
understood this multiple correspondence analysis.
I have 9 categorial variables with 15, 12,12,7,9,11,8 ,4 , 31 levels
respectively; that is 109 levels.
(*By the way, is there any problem because of having different levels at
each factor in the matrix of data ??*)
I want to know which are the levels (maybe i should say variables ? ) that
explain more variance in the set of categorical variables. After reading
help files i decided for
mydata.mjcaADJ <- mjca(mydata, lambda = "adj").
And now, i wanted to plot: plot(mydata.mjcaADJ, labels= c(0, 2),
col=c("white", "black"))
But I cannot see anything, as the labels superimpose. How could I see all
the labels?
It has occured to me to plot just the levels that have higher qualities. But
as I said I don't if this really makes sense, and if it had, how to select
this data in the commnad plot?
If it is needed that I upload my data, just tell me. Thanks in advance,
user at host.com
--
View this message in context:
http://r.789695.n4.nabble.com/plot-mjca-lambda-adjusted-tp4617675.html
Sent from the R help mailing list archive at Nabble.com.
