loess.sd | R Documentation |
Nonparametric estimation of mean function with variability bands.
loess.sd(x, y = NULL, nsigma = 1, ...)
panel.loess(x, y, col = par("col"), bg = NA, pch = par("pch"), cex = 1,
col.smooth = "red", span = 2/3, degree = 2, nsigma = 1, ...)
x |
a vector of values for the predictor variable |
y |
a vector of values for the response variable |
nsigma |
a multiplier for the standard deviation function. |
col, bg, pch, cex |
numeric or character codes for the color(s), point type and size of points; see also |
col.smooth |
color to be used by |
span |
smoothing parameter for |
degree |
the degree of the polynomials to be used, see |
... |
further argument passed to the function |
The function loess.sd
computes the loess smooth for the mean function and the mean plus and minus k
times the standard deviation function.
The function panel.loess
can be used to add to a scatterplot matrix panel a smoothing of mean function using loess with variability bands at plus and minus nsigmas
times the standard deviation.
Luca Scrucca luca.scrucca@unipg.it
Weisberg, S. (2005) Applied Linear Regression, 3rd ed., Wiley, New York, pp. 275-278.
loess
data(cars)
plot(cars, main = "lowess.sd(cars)")
lines(l <- loess.sd(cars))
lines(l$x, l$upper, lty=2)
lines(l$x, l$lower, lty=2)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.