summary.predcoca.Rdsummary methods for classes "predcoca" and
"symcoca". These provide a summary of the main results of a
Co-Correspondence Analysis model.
# S3 method for predcoca summary(object, axes = NULL, ...) # S3 method for symcoca summary(object, ...)
| object | an object of class |
|---|---|
| axes | numeric; how many axes to summarise? The default is to display 6 axes or all available axes, whichever is the smaller. |
| ... | arguments to be passed to other methods. |
A list with the some of the following components:
The site and/or species scores for the axes requested.
The call used to fit the model.
The eigenvalues for the axes requested. Not for
predcoca.simpls.
the names of the response and predictor either supplied by the user or derived from the original call.
a list with two components loadings1 and
loadings2, which refer to the response and the predictor
matrices respectively. (Only for predictive CoCA models.)
a list with components Yblock and
Xblock containing the amount of variance explained on each
CoCA axis in the response and the predictor respectively. (Only for
predictive CoCA models.)
a list with components Yblock and Xblock
containing the total variance in the response and the predictor data
sets respectively
a list with components total and residual
containing the total and residual inertia (variance) in the response
and the predictor matrices of a symmetric CoCA model. (Only for
symmetric CoCA models.)
the scaling used/requested. (Only for symmetric CoCA models.)
Gavin L. Simpson
The model fitting function coca
od <- options(digits = 4) ## symmetric CoCA data(beetles) data(plants) ## log transform the bettle data beetles <- log(beetles + 1) ## fit the model bp.sym <- coca(beetles ~ ., data = plants, method = "symmetric") #> #> Removed some species that contained no data in: beetles, plants summary(bp.sym) #> #> Symmetric Co-Correspondence Analysis #> #> Call: symcoca(y = y, x = x, n.axes = n.axes, R0 = weights, symmetric = #> symmetric, nam.dat = nam.dat) #> #> Inertia: #> Total Explained Residual #> beetles: 5.70 5.60 0.09 #> plants: 6.16 6.07 0.09 #> #> Eigenvalues: #> COCA 1 COCA 2 COCA 3 COCA 4 COCA 5 COCA 6 COCA 7 COCA 8 #> 5.91e-01 3.16e-01 2.03e-01 1.04e-01 6.69e-02 6.11e-02 5.26e-02 4.45e-02 #> COCA 9 COCA 10 COCA 11 COCA 12 COCA 13 COCA 14 COCA 15 COCA 16 #> 3.51e-02 2.31e-02 2.18e-02 1.43e-02 1.34e-02 1.10e-02 1.02e-02 8.39e-03 #> COCA 17 COCA 18 COCA 19 COCA 20 COCA 21 COCA 22 COCA 23 COCA 24 #> 7.44e-03 4.85e-03 4.15e-03 3.45e-03 2.82e-03 2.42e-03 2.26e-03 1.78e-03 #> COCA 25 COCA 26 COCA 27 COCA 28 COCA 29 #> 1.30e-03 1.06e-03 8.53e-04 2.93e-04 5.56e-05 ## Predictive CoCA bp.pred <- coca(beetles ~ ., data = plants) #> #> Removed some species that contained no data in: beetles, plants summary(bp.pred, axes = 1:2) #> #> Predictive Co-Correspondence Analysis #> #> Call: predcoca.simpls(y = y, x = x, R0 = weights, n.axes = n.axes, #> nam.dat = nam.dat) #> #> Percentage Variance Explained: #> #> Y-block: variance explained in beetles (response) #> Comp 1 Comp 2 Comp 3 Comp 4 Comp 5 Comp 6 Comp 7 Comp 8 #> Individual: 8.18 6.38 5.37 6.91 3.72 5.53 4.18 3.59 #> Cumulative: 8.18 14.56 19.93 26.84 30.56 36.10 40.27 43.87 #> Comp 9 Comp 10 Comp 11 Comp 12 Comp 13 Comp 14 Comp 15 #> Individual: 4.02 3.35 4.50 2.46 3.33 2.56 3.21 #> Cumulative: 47.89 51.24 55.73 58.19 61.52 64.08 67.29 #> Comp 16 Comp 17 Comp 18 Comp 19 Comp 20 Comp 21 Comp 22 #> Individual: 3.32 1.71 2.66 1.96 1.76 1.73 2.17 #> Cumulative: 70.60 72.31 74.97 76.93 78.69 80.42 82.59 #> Comp 23 Comp 24 Comp 25 Comp 26 Comp 27 Comp 28 Comp 29 #> Individual: 1.44 1.81 1.34 2.49 1.56 3.54 2.85 #> Cumulative: 84.02 85.84 87.18 89.67 91.22 94.76 97.61 #> #> X-block: variance explained in plants (predictor) #> Comp 1 Comp 2 Comp 3 Comp 4 Comp 5 Comp 6 #> Individual: 21.7114 16.2242 12.8109 5.4318 7.2780 3.7984 #> Cumulative: 21.7114 37.9356 50.7466 56.1784 63.4564 67.2548 #> Comp 7 Comp 8 Comp 9 Comp 10 Comp 11 Comp 12 #> Individual: 4.3291 4.2956 2.8320 2.8737 1.7862 2.4498 #> Cumulative: 71.5839 75.8795 78.7115 81.5852 83.3714 85.8212 #> Comp 13 Comp 14 Comp 15 Comp 16 Comp 17 Comp 18 #> Individual: 1.5557 1.6480 1.3222 1.1388 1.6991 0.8933 #> Cumulative: 87.3769 89.0249 90.3471 91.4859 93.1850 94.0783 #> Comp 19 Comp 20 Comp 21 Comp 22 Comp 23 Comp 24 #> Individual: 0.8779 0.8904 0.8645 0.6373 0.7220 0.5669 #> Cumulative: 94.9562 95.8466 96.7111 97.3484 98.0704 98.6373 #> Comp 25 Comp 26 Comp 27 Comp 28 Comp 29 #> Individual: 0.6544 0.3002 0.2774 0.0944 0.0362 #> Cumulative: 99.2918 99.5920 99.8694 99.9638 100.0000 options(od)