diffit: Aplication of the Diffit method.
In tuckerR.mmgg: Three-Mode Principal Components Analysis

Description Usage Arguments Details Value Author(s) References Examples

The diffit method is used to apply when we need to know the axis number to be gathered in the P mode, and Q mode. The third mode, K it is related to the environment numbers. The diffit method consist on fitting each value with the Tuckle algorithm.

1	diffit(datos, amb = 2, stand = TRUE, niter = 10000)

`datos`	datos original data from data frames
`amb`	numbers of environment
`stand`	a boolean value, if it is TRUE (value set by default) each variable is centered and scale by variable.
`niter`	the iteration number for the Tuckals algorithm, by default 10000 iteration.

The final result is the model which has the most coefficient diffits the greatest variability explained and the one which exceed the threshold.

saldiffit a list with a combination numbers of axis, percentage of variability explained and Diffit rate. The critic value or threhold is also return.

Marta Marticorena, Gustavo Gimenez, Cecilia Gonzalez, Sergio Bramardi

MARTICORENA, M.; BRAMARDI, S.; DEFACIO, R. 2010.: Characterization of maize populations in different environmental conditions by means of Three-Mode Principal Components Analysis. Revista Ciencia e Investigacion Agraria. 37(3): 93-105.
Timmerman, M.E., and H. Kiers. 2000.: Three-mode principal components analysis. Choosing numbers of components and sensitivity to local optima. The British Journal of the Mahematical and Statistical Psychology 53: 1-16.

#Copy and paste this example in your console without the comment
#data(maize_pop,package = "tuckerR.mmgg")
#dif_sal <- diffit(maize_pop,amb=2)
#print(dif_sal) the best combination is 3 3 2

tuckerR.mmgg documentation built on May 1, 2019, 11:22 p.m.