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

[David L Carlson]

We don't have enough information to replicate your results, but the warning in the output is suggestive: "Some constraints were aliased because they were collinear (redundant)".

Are some of your columns perfectly correlated with other columns? This could easily happen if there are more columns than rows.

-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352

-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Sanjay Kumar Jaiswal
Sent: Tuesday, July 18, 2017 4:08 AM
To: r-help at r-project.org
Subject: [R] Redundancy canonical analysis plot problem in 3D using VEGAN, RGL, SCATTERPLOT3D and SFSMISC

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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----------------------------------------------------------------------------------
Tshwane University of Technology
----------------------------------------------------------------------------------
This email is sent and received in terms of the Electronic
Communications Policy of Tshwane University of Technology.
In line with this policy, this email is private, privileged and
confidential. The full text of the Electronic Mail Disclaimer
can be seen on the TUT web site at
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