plot.cvsvd {bcv} | R Documentation |
Plot the result of cv.svd.gabriel
or
cv.svd.wold
, optionally with error bars.
## S3 method for class 'cvsvd' plot(x, errorbars = TRUE, add = FALSE, xlab = "Rank", ylab = "Mean Sq. Prediction Error", col = "blue", col.errorbars = "gray50", ...)
x |
the result of a |
errorbars |
indicates whether or not to add error bars. |
col |
the color to use for showing prediction error. |
col.errorbars |
the color to use for the error bars. |
add |
indicates whether or not to add to the current plot. |
xlab |
the label for the x axis. |
ylab |
the label for the y axis. |
... |
additional arguments for |
Plot the result of cv.svd.gabriel
or
cv.svd.wold
. This plots a the estimated prediction
error as a function of rank, optionally with error bars.
If add
is TRUE
, the current plot is not cleared.
Patrick O. Perry
cv.svd.gabriel
,
cv.svd.wold
,
print.cvsvd
summary.cvsvd
# generate a rank-2 matrix plus noise n <- 50; p <- 20; k <- 2 u <- matrix( rnorm( n*k ), n, k ) v <- matrix( rnorm( p*k ), p, k ) e <- matrix( rnorm( n*p ), n, p ) x <- u %*% t(v) + e # perform 5-fold Wold-style cross-validtion cvw <- cv.svd.wold( x, 5, maxrank=10 ) # perform (2,2)-fold Gabriel-style cross-validation cvg <- cv.svd.gabriel( x, 2, 2, maxrank=10 ) # plot the results par( mfrow=c(2,1) ) plot( cvw, main="Wold-style CV") plot( cvg, main="Gabriel-style CV")