rootogram {vcd} | R Documentation |
Rootograms of observed and fitted values.
rootogram(x, fitted, names = NULL, scale = c("sqrt", "raw"), type = c("hanging", "standing", "deviation"), bar.col = grey(0.7), line.col = 2, xlab = NULL, ylab = NULL, ylim = NULL, ...)
x |
either a vector or a 1-way table of frequencies. |
fitted |
a vector of fitted frequencies. |
names |
a vector of names passed to barplot, if set to
NULL the names of x are used. |
scale |
a character string indicating wether the values should be plotted on the raw or square root scale. |
type |
a character string indicating if the bars for the observed frequencies should be hanging or standing or indicate the deviation between observed and fitted frequencies. |
bar.col |
bar color (observed frequencies). |
line.col |
line color (fitted frequencies). |
xlab |
a label for the x axis. |
ylab |
a label for the y axis. |
ylim |
limits for the y axis. |
... |
further arguments passed to barplot . |
The observed frequencies are displayed as bars and the fitted frequencies as a line. By default a log scale is used to make the smaller frequencies more visible.
Achim Zeileis
J. W. Tukey (1977), Exploratory Data Analysis. Addison Wesley, Reading, MA.
M. Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.
## Simulated data examples: dummy <- rnbinom(200, size = 1.5, prob = 0.8) observed <- table(dummy) fitted1 <- dnbinom(as.numeric(names(observed)), size = 1.5, prob = 0.8) * sum(observed) fitted2 <- dnbinom(as.numeric(names(observed)), size = 2, prob = 0.6) * sum(observed) rootogram(observed, fitted1) rootogram(observed, fitted2) ## Real data examples: data(HorseKicks) HK.fit <- goodfit(HorseKicks) summary(HK.fit) plot(HK.fit) ## or equivalently rootogram(HK.fit) data(Federalist) F.fit <- goodfit(Federalist, type = "nbinomial") summary(F.fit) plot(F.fit)