Description Usage Arguments Details See Also Examples
Produces plots for the model basis vectors and the vectors forming the simplicity basis for the nearly null space, along with the variance-simplicity view and the percent of variance explained panel. Only six basis vectors can be displayed at a time.
1 2 |
x |
an object of class |
display |
a list. Specifies which model and simplicity basis vectors to plot.
Must be consistent with |
layout |
a matrix of locations for the component plots, following the format
used in the The subplots are drawn in the following order: first model then simple basis, followed by the variance-simplicity plot, and variance-explained last. |
... |
other parameters passed through to plotting functions |
The variance-simplicity view and the percent of variance explained
panel are always produced everytime plot.simpart
is called. The
variance-simplicity view plots the percent of variance explained and
the simplicity values of the basis vectors specified in
display
. If the number of basis vectors is greater than 6 and
the user specifies more than 6 in display
, an error message is
generated. In display
, non-existent basis numbers are ignored.
basisplot
, varsimp
, varperc
,
simpart
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | library(prinsimp)
require(graphics)
## Caterpillar estimated covariance matrix from Kingsolver et al (2004)
## Measurements are at temperatures 11, 17, 23, 29, 35, 40
data(caterpillar)
## Default plot method for a 2-dimensional nearly null space
cat.sim <- simpart(caterpillar, simpledim = 2,
x = c(11, 17, 23, 29, 35, 40), cov = TRUE)
plot(cat.sim)
## Plot only the two simplicity basis vectors in the 2-dimensional
## nearly null space
plot(cat.sim, display = list(simple=1:2))
## Try, by mistake to plot first four simple vectors when simpledim=2.
## Will plot only 2.
plot(cat.sim, display = list(simple=1:4))
## Only plot the first two model basis vectors, the variance simplicity
## view, and the percent variance explained panel using the 'layout'
## argument
plot(cat.sim, display = list(model=1:2), layout = matrix(1:4, nrow=2, ncol=2))
|
Warning message:
In subsplit(G, d - simpledim) :
G has negative eigenvalues, setting them to zero
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