CODEWITHSUNDEEP
rpcavegan
M. Beausoleil
M. Beausoleil

Reputation: 3555

RDA analysis in R gives error "attempt to set an attribute on NULL"

I'm running an analysis in R with the Vegan package. It's really simple in the way that I only want the summary to extract some values. But it keeps telling me an error message. Why?

I have this dataset 

feed.raw1 =structure(c(0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
            5L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 7L, 11L, 3L, 1L, 
            0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 
            0L, 0L, 0L, 0L, 3L, 0L, 5L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
            0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 8L, 7L, 5L, 1L, 
            0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 10L, 5L, 0L, 0L, 1L, 0L, 0L, 
            0L, 0L, 0L, 0L, 0L, 1L, 5L, 0L, 0L, 8L, 9L, 0L, 0L, 5L, 0L, 0L, 
            0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 15L, 0L, 
            51L, 10L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 
            0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 3L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
            0L, 0L, 0L, 45L, 203L, 17L, 54L, 4L, 1L, 0L, 0L, 0L, 0L, 10L, 
            9L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 12L, 0L, 
            0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 22L, 206L, 9L, 16L, 1L, 
            1L, 6L, 6L, 0L, 0L, 4L, 5L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
            0L, 7L, 0L, 0L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
            2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 12L, 3L, 1L, 0L, 
            0L, 0L, 0L, 0L, 0L, 0L, 23L, 4L, 1L, 2L, 0L, 2L, 0L, 0L, 0L, 
            0L, 0L, 0L, 0L, 0L, 76L, 0L, 96L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
            11L, 0L, 3L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 270L, 
            144L, 7L, 8L, 15L, 6L, 6L, 2L, 6L, 1L, 25L, 5L, 0L, 1L, 1L, 0L, 
            0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 14L, 2L, 1L, 0L, 0L, 0L, 0L, 
            0L, 3L, 0L, 0L, 0L, 3L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
            0L, 2L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 1L, 0L, 
            0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 7L, 0L, 0L, 0L, 0L, 0L, 
            0L, 14L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 
            0L, 0L), .Dim = c(12L, 32L), .Dimnames = list(c("a", "b", "c", 
                                                            "d", "e", "f", "g", "h", "i", "j", "k", "l"), c("a", "b", "c", 
                                                                                                            "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", 
                                                                                                            "q", "r", "s", "t", "u", "v", "w", "x", "y", "z", "a1", "b1", 
                                                                                                            "c1", "d1", "e1", "f1")))

And I'm running this analysis: 

library(vegan)
feed_raw.hel = decostand(feed.raw1, method = "pa")

pca.feed=vegan::rda(feed_raw.hel, scale=FALSE) 
head(summary(pca.feed))

It gives me this error: 

Canonical correspondence analysis

Class: rda cca
Call: rda(X = feed_raw.hel, scale = FALSE)

Total inertia: 0

Eigenvalues:
Error in names(vec) <- paste("Ax", 1:length(vec), sep = "") : 
  attempt to set an attribute on NULL

Upvotes: 0

Views: 3551

Answers (2)

PhilMo
PhilMo

Reputation: 11

I also had this problem and finally figured out that, in my case at least, another package (ade4) also has a cca function that was masking the cca function in vegan. This is mentioned in the help files somewhat vaguely. I fixed this issue on my code by restarting my R session (in RStudio) and calling the libraries in this order:

library(ade4)
library(vegan)

Then the vegan::cca function takes president over the ade4::cca function.

Upvotes: 1

fishtank
fishtank

Reputation: 3728

No error found (see comments in the OP):

> library(vegan)
> feed_raw.hel = decostand(feed.raw1, method = "pa")
>
> pca.feed=vegan::rda(feed_raw.hel, scale=FALSE)
> head(summary(pca.feed))

Call:
rda(X = feed_raw.hel, scale = FALSE)

Partitioning of variance:
              Inertia Proportion
Total           5.394          1
Unconstrained   5.394          1

Eigenvalues, and their contribution to the variance

Importance of components:
                         PC1    PC2    PC3    PC4     PC5     PC6     PC7
Eigenvalue            2.0696 0.7676 0.6639 0.5502 0.41578 0.31941 0.22209
Proportion Explained  0.3837 0.1423 0.1231 0.1020 0.07708 0.05922 0.04117
Cumulative Proportion 0.3837 0.5260 0.6491 0.7511 0.82817 0.88739 0.92856
                          PC8     PC9    PC10    PC11
Eigenvalue            0.15383 0.11310 0.07857 0.03984
Proportion Explained  0.02852 0.02097 0.01457 0.00739
Cumulative Proportion 0.95708 0.97805 0.99261 1.00000

Scaling 2 for species and site scores
* Species are scaled proportional to eigenvalues
* Sites are unscaled: weighted dispersion equal on all dimensions
* General scaling constant of scores:  2.775394


Species scores

          PC1      PC2      PC3      PC4        PC5      PC6
a    -0.03289 -0.13245  0.18066  0.12616 -0.2028751  0.07257
b    -0.19170 -0.26686 -0.20142 -0.16621  0.0739356 -0.16726
c    -0.43542 -0.24013 -0.02194  0.16668 -0.0037653  0.18018
d    -0.43702  0.08614 -0.05548 -0.06814 -0.0009418 -0.03947
e    -0.24815 -0.06070  0.29795  0.18439 -0.0879021 -0.02246
f     0.08852  0.11597 -0.07947  0.02250 -0.0926734 -0.13060
....                                                    


Site scores (weighted sums of species scores)

          PC1      PC2      PC3     PC4     PC5     PC6
a    -1.65813  0.55267  0.90341  0.4485  0.8856 -0.7321
b    -1.70818  0.11084 -1.33080 -0.9734 -0.8929  0.4280
c    -0.25333 -1.02024  1.39160  0.9718 -1.5627  0.5590
d    -0.09478 -1.47685 -1.03494  1.1078  1.2228 -0.2536
e     0.26417  0.60502  0.71856 -0.6194  1.1614  1.2200
f     0.36048 -0.01608 -0.09826 -0.2709  0.3182  1.3866
....

Upvotes: 1

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