summary.predcoca: Summarizing Co-CA Model Fits

In cocorresp: Co-correspondence analysis methods

Description

summary methods for classes "predcoca" and "symcoca". These provide a summary of the main results of a Co-Correspondence Analysis model.

Usage

## S3 method for class 'predcoca'
summary(object, axes = c(1:min(6, object$n.axes)),
         display = c("species", "sites"), ...)

## S3 method for class 'symcoca'
summary(object, axes = c(1:min(6, object$n.axes)),
        display = c("species", "sites"), scaling = 1, ...)

Arguments

object	an object of class "predcoca" or "symcoca". Generally the result of a call to coca.
axes	the number of CoCA axes to return in the result set.
display	one or both of "species" and/or "sites"
scaling	for objects of class "symcoca" only, the scaling to be applied to the results. One of "1" or "2". See below for details of scalings used.
...	arguments to be passed to other methods.

Value

A list with the some of the following components:

cocaScores	The site and or species scores for the axes requested.
call	The call used to fit the model.
lambda	The eigenvalues for the axes requested. Not for predcoca.simpls.
namY, namX	the names of the response and predictor either supplied by the user or derived from the original call.
loadings	a list with two components loadings1 and loadings2, which refer to the response and the predictor matrices respectively. (Only for predictive CoCA models.)
varianceExp	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.)
totalVar	a list with components Yblock and Xblock containing the total variance in the response and the predictor data sets respectively
inertia	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.)
scaling	the scaling used/requested. (Only for symmetric CoCA models.)

Author(s)

Gavin L. Simpson

See Also

The model fitting function coca

Examples

## 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")
summary(bp.sym, axes = 1:4)

## Different scaling
summary(bp.sym, axes = 1:4, scaling = 2)

## Predictive CoCA
bp.pred <- coca(beetles ~ ., data = plants)
summary(bp.pred, axes = 1:2)

cocorresp documentation built on May 2, 2019, 5:16 p.m.