Print an mspca Object

S3 print method for objects of class "mspca" returned by mspca(). Displays the sparse loading matrix (restricted to the union of non-zero rows) together with the percentage of variance explained and the number of non-zero loadings per component.

Usage

# S3 method for class 'mspca'
print(x, C = NULL, digits = NULL, ...)

Arguments

x

An object of class "mspca", as returned by mspca().

C

(optional) A numeric matrix (p x p). The covariance or correlation matrix used when fitting. Not required: mspca() stores the per-PC variance figures and the variable names on the fitted object, for both input types. Supplying C recomputes the variance figures from it and takes the row labels from its dimnames.

digits

An integer or NULL. Number of significant digits for display. When NULL (the default), getOption("digits") is used, so the output respects options(digits = ...).

...

Further arguments required by the print() generic; not used by this method.

Value

Invisibly returns x.

Details

When the model was fit from a covariance/correlation matrix (type = "Sigma"), pass that matrix as C so that per-PC variance figures can be computed; when it was fit from a raw data matrix (type = "X"), C may be omitted because the figures are stored inside the object.

Examples

TestMat <- cor(mtcars)
res <- mspca(TestMat, r = 2, ks = c(4, 4), verbose = FALSE)
print(res)
#> 
#> msPCA solution: 2 sparse PCs
#> Pct. variance explained: 32.19810 27.98031 
#> Non-zero loadings per PC: 4 4 
#> 
#> Sparse PCs
#>            [,1]       [,2]
#> mpg   0.5231892  0.0000000
#> cyl  -0.4135157  0.0000000
#> disp -0.5327976  0.0000000
#> hp    0.0000000 -0.5180501
#> wt   -0.5209650  0.0000000
#> qsec  0.0000000  0.5056638
#> vs    0.0000000  0.4935986
#> carb  0.0000000 -0.4819634