topmodels {topmodels} | R Documentation |
Plotting methods for probabilistic (regression) model objects supported by procast
.
topmodels(object, flavor = NULL, newdata = NULL, na.action = na.pass, which = NULL, ask = dev.interactive(), spar = TRUE, pages = NULL, ...)
object |
An object supported by |
flavor |
Should the rootogram be a |
newdata |
optionally, a data frame in which to look for variables with which to predict. If omitted, the original observations are used. |
na.action |
function determining what should be done with missing
values in |
which |
Character or integer, selects the type of plot: |
ask |
For multiple plots, the user is asked to show the next plot. |
spar |
Should graphical parameters be set? |
pages |
For numeric one, all plots will be shown on a single page. |
... |
Arguments to be passed to |
FIXME
FIXME
data("CrabSatellites", package = "countreg") CrabSatellites2 <- CrabSatellites[CrabSatellites$satellites <= 1, ] m1 <- glm(satellites ~ width + color, data = CrabSatellites, family = poisson) m2 <- glm(satellites ~ width + color, data = CrabSatellites2, family = binomial) ## base graphics topmodels(m1, pages = 1, flavor = "base") topmodels(m1, pages = 1, nsim = 10, flavor = "base") topmodels(m1, pages = 1, nsim = 30, fill = 2, flavor = "base") topmodels(m1, pages = 1, nsim = 30, ref = 2, flavor = "base") topmodels(m1, pages = 1, nsim = 30, fill =2, add_hist = 2, flavor = "base") ## ggplot2 graphics topmodels(m1, pages = 1, nsim = 30, flavor = "tidyverse") topmodels(m2, pages = 1, nsim = 30, flavor = "tidyverse")