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plot.fpcr: Default plotting for functional principal component regression output

Description

Inputs an object created by fpcr, and plots the estimated coefficient function.

Usage

## S3 method for class 'fpcr':
plot(x, se=TRUE, col=1, lty=c(1,2,2), xlab="", 
                    ylab="Coefficient function", ...)

Arguments

x
an object of class "fpcr".
se
if TRUE (the default), upper and lower lines are added at 2 standard errors (in the Bayesian sense; see Wood, 2006) above and below the coefficient function estimate. If a positive number is supplied, the standard error is instead multiplied
col
color for the line(s). This should be either a number, or a vector of length 3 for the coefficient function estimate, lower bound, and upper bound, respectively.
lty
line type(s) for the coefficient function estimate, lower bound, and upper bound.
xlab, ylab
x- and y-axis labels.
...
other arguments passed to the underlying plotting function.

Value

  • None; only a plot is produced.

References

Wood, S. N. (2006). Generalized Additive Models: An Introduction with R. Boca Raton, FL: Chapman & Hall.

See Also

fpcr, which includes an example.