objplot {pcaPP} | R Documentation |
Objective Function Plot for Sparse PCs
Description
Plots an objective function (TPO or BIC) of one or more sparse PCs for a series of lambdas.
Usage
objplot (x, k, ...)
Arguments
x |
|
k |
This function displays the objective function's values of the
|
... |
Further arguments passed to or from other functions. |
Details
This function operates on the return object of function
opt.TPO
or opt.BIC
.
The model (lambda
) selected by the minimization of the corresponding
criterion is highlighted by a dashed vertical line.
The component the argument k
refers to, corresponds to the
$pc.noord
item of argument x
.
For more info on the order of sparse PCs see the details section of
opt.TPO
.
Author(s)
Heinrich Fritz, Peter Filzmoser <P.Filzmoser@tuwien.ac.at>
References
C. Croux, P. Filzmoser, H. Fritz (2011). Robust Sparse Principal Component Analysis Based on Projection-Pursuit, ?? To appear.
See Also
Examples
set.seed (0)
## generate test data
x <- data.Zou (n = 250)
k.max <- 3 ## max number of considered sparse PCs
## arguments for the sPCAgrid algorithm
maxiter <- 25 ## the maximum number of iterations
method <- "sd" ## using classical estimations
## Optimizing the TPO criterion
oTPO <- opt.TPO (x, k.max = k.max, method = method, maxiter = maxiter)
## Optimizing the BIC criterion
oBIC <- opt.BIC (x, k.max = k.max, method = method, maxiter = maxiter)
## Objective function vs. lambda
par (mfrow = c (2, k.max))
for (i in 1:k.max) objplot (oTPO, k = i)
for (i in 1:k.max) objplot (oBIC, k = i)