panel.cbH: Lattice panels for error bars and envelop bands

In walmes/wzRfun: Walmes Zeviani's collection of functions

Description

Used to plot confidence bars or confidence bands in lattice plots.

Usage

panel.cbH(
  x,
  y,
  ly,
  uy,
  subscripts,
  cty,
  col.line = plot.line$col,
  lwd = plot.line$lwd,
  desloc = NULL,
  fill = 1,
  alpha = 0.1,
  length = 0.05,
  ...
)

prepanel.cbH(y, ly, uy, subscripts)

Arguments

x, subscripts, col.line, lwd, ...	arguments passed to xyplot().
y	central value (point estimate).
ly	lower limit.
uy	upper limit.
cty	string that is the confidence type. Values current acepted are "bars" for error bars (confidence intervals) and "bands" for confidence/envelop bands.
desloc	a numeric vetor with length equal to y used to desloc vertically the values to avoid overlapping with points or others factor levels intervals.
fill	a color to fill the polygon defined by the confidence bands. Default is 1 that is the black color. Not used when cty = "bars".
alpha	transparecy level for the polygon defined by the confidence bands. Default is 0.1. Not used when cty = "bars".
length	is the length of the upper/lower error bars whiskers. Default is 0.05. Not used when cty = "bands".

Value

None is returned.

Author(s)

Walmes Zeviani, [e-mail], based on the R-help mail list.

Examples

library(lattice)
library(latticeExtra)

#--------------------------------------------

m0 <- lm(sqrt(dist) ~ speed, data = cars)
pred <- with(cars,
             data.frame(speed = seq(min(speed), max(speed),
                                    length.out = 20)))
aux <- predict(m0, newdata = pred, interval = "confidence")
pred <- cbind(pred, aux)

xyplot(sqrt(dist) ~ speed, data = cars,
       ylab = expression(sqrt(distance)),
       xlab = "Speed") +
    as.layer(xyplot(fit ~ speed, data = pred, type = "l",
                    ly = pred$lwr, uy = pred$upr,
                    cty = "bands", fill = "blue", alpha = 0.3,
                    prepanel = prepanel.cbH,
                    panel = panel.cbH))

#--------------------------------------------

m1 <- lm(weight ~ feed, data = chickwts)
pred <- with(chickwts, data.frame(feed = levels(feed)))
aux <- predict(m1, newdata = pred, interval = "confidence")
pred <- cbind(pred, aux)

xyplot(weight ~ feed, data = chickwts,
       xlab = "Feed", ylab = "Weight") +
    as.layer(xyplot(fit ~ feed, data = pred,
                    ly = pred$lwr, uy = pred$upr, cty = "bars",
                    desloc = rep(0.15, length(pred$fit)),
                    prepanel = prepanel.cbH,
                    panel = panel.cbH))

#-----------------------------------------------------------------------

set.seed(123)
da <- expand.grid(trt = gl(2, 1), x = 1:7)
da$y <- with(da, as.integer(trt) + 0.5 * x + rnorm(x, 0, 0.3))
xyplot(y ~ x, groups = trt, data = da)

m2 <- lm(y ~ trt + x, data = da)

pred <- with(da,
             expand.grid(trt = levels(trt),
                         x = seq(min(x), max(x), length.out = 20)))
aux <- predict(m2, newdata = pred, interval = "confidence")
pred <- cbind(pred, aux)

xyplot(y ~ x, groups = trt, data = da) +
    as.layer(xyplot(fit ~ x, groups = trt, data = pred, type = "l",
                    ly = pred$lwr, uy = pred$upr,
                    cty = "bands", alpha = 0.75,
                    prepanel = prepanel.cbH,
                    panel = panel.superpose,
                    panel.groups = panel.cbH),
             under = TRUE)

walmes/wzRfun documentation built on Aug. 10, 2021, 2:19 p.m.