GPA.test: Significance test for GPA

In RVAideMemoire: Testing and Plotting Procedures for Biostatistics

Significance test for GPA

Description

Performs a permutation significance test based on total variance explained for Generalized Procrustes Analysis. The function uses GPA.

Usage

GPA.test(df, group, tolerance = 10^-10, nbiteration = 200, scale = TRUE,
  nperm = 999, progress = TRUE)

Arguments

df	a data frame with n rows (individuals) and p columns (quantitative varaibles), in which all data frames are combined.
group	a vector indicating the number of variables in each group (i.e. data frame).
tolerance	a threshold with respect to which the algorithm stops, i.e. when the difference between the GPA loss function at step n and n+1 is less than tolerance.
nbiteration	the maximum number of iterations until the algorithm stops.
scale	logical, if TRUE (default) scaling is required.
nperm	number of permutations.
progress	logical indicating if the progress bar should be displayed.

Details

Rows of each data frame are randomly and independently permuted.

The function deals with the limitted floating point precision, which can bias calculation of p-values based on a discrete test statistic distribution.

Value

method	a character string indicating the name of the test.
data.name	a character string giving the name(s) of the data, plus additional information.
statistic	the value of the test statistics.
permutations	the number of permutations.
p.value	the p-value of the test.

Author(s)

Maxime HERVE <[e-mail]>

References

Wakeling IN, Raats MM and MacFie HJH (1992) A new significance test for consensus in Generalized Procrustes Analysis. Journal of Sensory Studies 7:91-96.

See Also

GPA

Examples

require(FactoMineR)
data(wine)

## Not run: GPA.test(wine[,-(1:2)],group=c(5,3,10,9,2))

RVAideMemoire documentation built on Nov. 6, 2023, 5:07 p.m.