print.tunelocal {CA3variants}

Print of tunelocal function results

Description

This function prints the results of tunelocal for choosing the optimal model dimension of a variant of three-way correspondence analysis. When boots = T the number of different models that is assessed is based on the size of the original data being analysed.
For example, for a 4 x 5 x 4, there are 80 different models that are assessed.
When boots = T, the number of different models that is assessed is based on the size of all models
obtained from the combination of dimensions of the bootstrapped data.
For example, for a 4 x 5 x 4 array, there are 800 different models that are assessed. By defaultnboots = 100,
you can change the parameter value in input of tunelocal function.

Usage

## S3 method for class 'tunelocal'
print(x, digits = 3,...)

Arguments

x

The name of the output of the function tunelocal.

digits

The input parameter specifying the digital number. By default, digits = 3.

...

Further arguments passed to or from other methods.

Value

The value of output returned depends on the kind of sampling chosen. The sampling for making the convex hull can be based on the original data or on the bootstrapped data samples. In detail:

XG

The data samples used for assessing the optimal model dimension (original and/or bootstrapped).

output1

The results of tunelocal. It gives the goodness-of-fit criteria of models that are located
on the boundary of the convex hull and selects the optimal model by means of the scree test values (st);
see Ceulemans and Kiers (2006).

ca3type

It gives information about the kind of variant of three-way CA considered.

boots

The flag parameter to perform the search of optimal dimensions using bootstrap samples. By defaults, boots = FALSE.

Author(s)

Rosaria Lombardo, Michel van de Velden and Eric J. Beh.

References

Wilderjans T F, Ceulemans E, and Meers K (2013) CHull: A generic convex hull based model selection method. Behavior Research Methods, 45, 1-15.
Ceulemans E, and Kiers H A L (2006) Selecting among three-mode principal component models of different types and complexities: A numerical convex hull based method. British Journal of Mathematical & Statistical Psychology, 59, 133-150.

Examples

res.tunelocal<-tunelocal(happy, ca3type = "CA3") 
print(res.tunelocal)