plot.fpcr {refund}

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 by this number.

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.

Author(s)

Philip Reiss [e-mail]

References

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

See Also

fpcr, which includes an example.