Displaying 6 results from an estimated 6 matches for "mjca".
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mca
2008 Mar 09
0
[ca package] how to extract x,y from mjca function
Hi,
I would like to extract x,y from mjca function in ca package to be able to
draw other graph types.
For example for simple mca function from MASS I can do the following:
-------------
mydata.mca <- mca(anydata, nf = 2, abbrev = TRUE)
x <- anydata.mca$rs[,1] #that is what I can 'extract'
y <- anydata.mca$rs[,2]
pl...
2008 Mar 10
0
[ca package] access to any x/y in mjca function
Hi,
I would like to extract x,y from mjca function in ca package to be able to
draw other graph types.
For example for simple mca function from MASS I can do the following:
-------------
anydata.mca <- mca(anydata, nf = 2, abbrev = TRUE)
x <- anydata.mca$rs[,1] #that is what I can 'extract'
y <- anydata.mca$rs[,2]
p...
2012 May 08
0
plot mjca lambda = "adjusted"
...s.
(*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 tha...
2013 Feb 26
1
How to avoid overlapping labels
...identify the xy
coordinates for each point first and then manually move every point? and if
i neet to do so how to use the identify() function?
or is there any possibility to automatically place the labels in the best
position?
>MatArab <- as.matrix(ende[2:12])
>MatArab
>MCAArab <- mjca(MatArab, nd = 2, lambda = "JCA", maxit = 50, epsilon =
0.0001)
>plot(MCAArab, dim = c(1,2), map = "symmetric", centroids = TRUE,
+ what = c("none", "all"), mass = c(FALSE, FALSE),
+ contrib = c("none", "none"), col = c("#000000&...
How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction
2011 Aug 17
4
How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction
...% 50% 75% 100%
53.00 66.75 72.00 76.25 85.00
> age_Q <- cut(x17.df$age, right=TRUE, breaks=c(-Inf, 66, 72, 76, Inf),
labels=c("53-66", "67-72", "73-76", "77-85"))
> table(age_Q)
age_Q
53-66 67-72 73-76 77-85
26 27 25 26
Then, I used mjca of ca pacakge for MCA.
> mjca1 <- mjca(mydata.df[, c("age_Q","sex","symptom", "HT", "DM",
"IHD","smoking","DL", "Statin")])
> summary(mjca1)
Principal inertias (eigenvalues):
dim value %...
2012 Mar 09
1
Multiple Correspondence Analysis
...alculate
> the dependence between all of them. That's why I am going for a
> dependence matrix. Where am I wrong?
>
>
> After that I can proceed with the MCA. Of course, I would also
> need help there.
>
> I used the following codes to do it:
>
> /spain.mca <- mjca(spain) /#it makes the mca for all the data
> /spain.mca/
> /plot(spain.mca)/ #it shows the plot
>
> But the plot was overcrowded. Anyway, I must first complete the first
> step, this was just to make some practice on it.
>
> As you can see, until now I didn't succeed.
>...