Provides default values for many arguments available for
plotvgam()
.
plotvgam.control(which.cf = NULL,
xlim = NULL, ylim = NULL, llty = par()$lty, slty = "dashed",
pcex = par()$cex, pch = par()$pch, pcol = par()$col,
lcol = par()$col, rcol = par()$col, scol = par()$col,
llwd = par()$lwd, slwd = par()$lwd, add.arg = FALSE,
one.at.a.time = FALSE, .include.dots = TRUE, noxmean = FALSE,
shade = FALSE, shcol = "gray80", main = "", ...)
A list with values matching the arguments.
Integer vector specifying which component functions are to be plotted (for each covariate). Must have values from the set {1,2,...,\(M\)}.
Range for the x-axis.
Range for the y-axis.
Line type for the fitted functions (lines).
Fed into par(lty)
.
Line type for the standard error bands.
Fed into par(lty)
.
Character expansion for the points (residuals).
Fed into par(cex)
.
Character used for the points (residuals).
Same as par(pch)
.
Color of the points.
Fed into par(col)
.
Color of the fitted functions (lines).
Fed into par(col)
.
Color of the rug plot.
Fed into par(col)
.
Color of the standard error bands.
Fed into par(col)
.
Line width of the fitted functions (lines).
Fed into par(lwd)
.
Line width of the standard error bands.
Fed into par(lwd)
.
Logical.
If TRUE
then the plot will be added to an existing
plot, otherwise a new plot will be made.
Logical. If TRUE
then the plots are done
one at a time, with the user having to hit the return key
between the plots.
Not to be used by the user.
Logical. If TRUE
then the point at the mean of \(x\),
which is added when
standard errors are specified and
it thinks the function is linear,
is not added.
One might use this argument if ylab
is specified.
shade
is logical; if TRUE
then
the pointwise SE band is shaded gray by default.
The colour can be adjusted by setting shcol
.
These arguments are ignored unless
se = TRUE
and overlay = FALSE
;
If shade = TRUE
then scol
is ignored.
Character vector, recycled to the number needed.
Other arguments that may be fed into par()
.
In the above, \(M\) is the number of linear/additive predictors.
Thomas W. Yee
The most obvious features of plotvgam
can be
controlled by the above arguments.
Yee, T. W. and Wild, C. J. (1996). Vector generalized additive models. Journal of the Royal Statistical Society, Series B, Methodological, 58, 481--493.
plotvgam
.
plotvgam.control(lcol = c("red", "blue"), scol = "darkgreen", se = TRUE)
Run the code above in your browser using DataLab