x
removed from their names.xhistogram(x, data=NULL, panel=panel.xhistogram, type="density", ...)xqqmath(x, data=NULL, panel="panel.xqqmath", ...)
panel.xqqmath(x, qqmathline = !(fitline || idline), idline = FALSE, fitline = FALSE,
slope = NULL, intercept = NULL, overlines = FALSE, groups=NULL, ...,
col.line = trellis.par.get("add.line")$col, pch = 16, lwd = 2,
lty = 2 )
panel.xhistogram(x,
dcol = trellis.par.get("plot.line")$col, dlwd = 2,
gcol = trellis.par.get("add.line")$col, glwd = 2,
fcol = trellis.par.get("superpose.polygon")$col,
dmath = dnorm,
verbose = FALSE,
dn = 100, args = NULL, labels = FALSE, density = FALSE, fit = NULL,
start = NULL, type = "density", v, h, groups=NULL, breaks,
stripes=c('vertical','horizontal','none'), alpha=1, ...)
dnorm
dmath
panel.qqmathline
slope
and intercept
.fitline
. If NULL (the default)
the mean of the data is used, which works well
for normal-quantile plots but may not be what you want for fitting
other distributions.fitline
.
If NULL (the default),
the standard deviation of the data is used, which works well
for normal-quantile plots but may not be what you want for fitting
other distributions.col
but applied only to linescol
and lwd
but applied to density curvescol
and lwd
but applied to grid linesfitdistr
from MASS
for maximum-likelihood fittinglattice
plotslattice
plotsfitdistr
q
,
p
,
which
,
main
which behave as in other lattice
graphics functionshistogram
,
pnorm
,
qnorm
,
qqmath
, and
plot
.x <- rnorm(200)
xhistogram(~ x, groups = x > 2, n=20, density=TRUE )
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