[R] Redundancy canonical analysis plot problem in 3D using VEGAN, RGL, SCATTERPLOT3D and SFSMISC

Jeff Newmiller jdnewmil at dcn.davis.ca.us
Tue Jul 18 17:38:19 CEST 2017


I don't know much about what you are doing with your data,  but I do know that your example is not reproducible  [1][2][3].

It is very important to be clear both to yourself and to anyone you ask to help you what your data are like. Details like what the column names are, whether they are numeric, character, factor, etc., can completely alter the result. The dput() function can be used to share just enough of your data or a simulated version of it so that we can run your statements also, or point out that your data were imported incorrectly in the first place. 

Also, do read the Posting Guide mentioned in the footer of this email. This is a plain text mailing list so what you saw when you sent it (HTML formatted) is not what we saw (see below)... but if you post in plain text format we are much more likely to solve your problem without back and forth about what you really meant. 

[1] http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example

[2] http://adv-r.had.co.nz/Reproducibility.html

[3] https://cran.r-project.org/web/packages/reprex/index.html (read the vignette)
-- 
Sent from my phone. Please excuse my brevity.

On July 18, 2017 2:08:04 AM PDT, Sanjay Kumar Jaiswal <JaiswalSK at tut.ac.za> wrote:
>Hello Sir
>
>I am getting problem in plotting in CCA . Could you please help me? I
>wrote the below command but I don't know why it is taking only first 5
>env data rather than all 9.
>
>> strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName="strain", header
>= T, row.names = 1)
>> env.data <- read.xlsx("Dee rhiz.xlsx", sheetName="env", header = T,
>row.names = 1)
>> strain.cca <- cca(strain.data ~
>Ph+TotalN+Organicmatter+Ca+K+Na+P+Cu+Mn, data=env.data)
>> strain.cca
>Call: cca(formula = strain.data ~ Ph + TotalN + Organicmatter + Ca + K
>+ Na + P
>+ Cu + Mn, data = env.data)
>
>              Inertia Proportion Rank
>Total               5          1
>Constrained         5          1    5
>Unconstrained       0          0    0
>Inertia is mean squared contingency coefficient
>Some constraints were aliased because they were collinear (redundant)
>
>Eigenvalues for constrained axes:
>CCA1 CCA2 CCA3 CCA4 CCA5
>   1    1    1    1    1
>
>
>> plot(strain.cca)
>
>> summary (strain.cca)
>
>
>
>Call:
>
>cca(formula = strain.data ~ Ph + TotalN + Organicmatter + Ca +      K +
>Na + P + Cu + Mn, data = env.data)
>
>
>
>Partitioning of mean squared contingency coefficient:
>
>              Inertia Proportion
>
>Total               5          1
>
>Constrained         5          1
>
>Unconstrained       0          0
>
>
>
>Eigenvalues, and their contribution to the mean squared contingency
>coefficient
>
>
>
>Importance of components:
>
>                      CCA1 CCA2 CCA3 CCA4 CCA5
>
>Eigenvalue             1.0  1.0  1.0  1.0  1.0 0
>
>Proportion Explained   0.2  0.2  0.2  0.2  0.2 0
>
>Cumulative Proportion  0.2  0.4  0.6  0.8  1.0 1
>
>
>
>Accumulated constrained eigenvalues
>
>Importance of components:
>
>                      CCA1 CCA2 CCA3 CCA4 CCA5
>
>Eigenvalue             1.0  1.0  1.0  1.0  1.0
>
>Proportion Explained   0.2  0.2  0.2  0.2  0.2
>
>Cumulative Proportion  0.2  0.4  0.6  0.8  1.0
>
>
>Biplot scores for constraining variables
>
>
>
>                  CCA1     CCA2    CCA3    CCA4     CCA5
>
>Ph             0.29757  0.85775 -0.3364  0.2242 -0.11088
>
>TotalN        -0.01537 -0.67797  0.6132  0.2831  0.28985
>
>Organicmatter  0.14618  0.06462  0.8320  0.3515  0.39827
>
>Ca             0.08310 -0.41940  0.3858  0.8116  0.09834
>
>K              0.37548  0.38360  0.6849 -0.4172  0.26222
>
>
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>
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>Tshwane University of Technology
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