bootstrapCP: Bootstrap percentile intervals for CANDECOMP/PARAFAC

In ThreeWay: Three-Way Component Analysis

Description

Produces percentile intervals for all output parameters. The percentile intervals indicate the instability of the sample solutions.

Usage

 
 bootstrapCP(X, A, B, C, n, m, p, r, ort1, ort2, ort3, conv, centopt, normopt, 
  scaleopt, maxit, laba, labb, labc)

Arguments

X	Matrix (or data.frame coerced to a matrix) of order (n x mp) containing the matricized array (frontal slices)
A	Component matrix for the A-mode
B	Component matrix for the B-mode
C	Component matrix for the C-mode
n	Number of A-mode entities of X
m	Number of B-mode entities of X
p	Number of C-mode entities of X
r	Number of extracted components
ort1	Type of constraints on A (see CP)
ort2	Type of constraints on B (see CP)
ort3	Type of constraints on C (see CP)
conv	Convergence criterion
centopt	Centering option (see cent3)
normopt	Normalization option (see norm3)
scaleopt	Scaling option (see renormsolCP)
maxit	Maximal number of iterations
laba	Optional vector of length n containing the labels of the A-mode entities
labb	Optional vector of length m containing the labels of the B-mode entities
labc	Optional vector of length p containing the labels of the C-mode entities

Value

A list including the following components:

Bint	Bootstrap percentile interval of every element of B
Cint	Bootstrap percentile interval of every element of C
fpint	Bootstrap percentile interval for the goodness of fit index expressed as a percentage

Note

The preprocessing must be done in same way as for sample analysis.
The resampling mode must be the A-mode.
The starting points for every bootstrap solution are two: rational (using SVD) and solution from the observed sample.

Author(s)

Maria Antonietta Del Ferraro [e-mail]
Henk A.L. Kiers [e-mail]
Paolo Giordani [e-mail]

References

H.A.L. Kiers (2004). Bootstrap confidence intervals for three-way methods. Journal of Chemometrics 18:22–36.

See Also

bootstrapT3, CP, percentile95

Examples

data(TV)
TVdata=TV[[1]]
labSCALE=TV[[2]]
labPROGRAM=TV[[3]]
labSTUDENT=TV[[4]]
# permutation of the modes so that the A-mode refers to students
TVdata <- permnew(TVdata, 16, 15, 30)
TVdata <- permnew(TVdata, 15, 30, 16)
# CP solution
TVcp <- CPfuncrep(TVdata, 30, 16, 15, 2, 1, 1, 1, 0, 1e-6, 10000)
## Not run: 
# Bootstrap analysis on CP solution
boot <- bootstrapCP(TVdata, TVcp$A, TVcp$B, TVcp$C, 30, 16, 15, 2, 1, 1, 1, 
 1e-6, 0, 0, 0, 10000, labSTUDENT, labSCALE, labPROGRAM)
# Bootstrap analysis on CP solution (when labels are not available)
boot <- bootstrapCP(TVdata, TVcp$A, TVcp$B, TVcp$C, 30, 16, 15, 2, 1, 1, 1, 
 1e-6, 0, 0, 0, 10000)

## End(Not run)

ThreeWay documentation built on May 2, 2019, 9:20 a.m.