Plot a fitted panglm hurdle model

Displays coefficient estimates and Wald confidence intervals for the binary hurdle component, the positive-count component, or both, in the dot-and-whisker layout of plot.panglm(). which = "correlation" draws the heatmap of the correlation matrix of all the estimates (see plot.panglm()); the two parts are estimated separately, so the between-part block is zero.

Usage

# S3 method for class 'panglm_hurdle'
plot(
  x,
  which = c("both", "zero", "count", "correlation"),
  level = 0.95,
  parm = NULL,
  cells = FALSE,
  ...
)

Arguments

x

a fitted "panglm_hurdle" object

which

one of "both", "zero", "count" or "correlation"

level

confidence level for coefficient intervals

parm

names or positions of the terms to plot; by default every term except "(Intercept)". For "correlation", names as in coef(x) (with the zero: and count: prefixes).

cells

for "correlation", print the correlation in each cell

...

additional arguments passed to graphics::plot.default()

Value

x, invisibly

See also

Other panhurdle methods: hurdle-methods

Examples

data(copd)
fit <- panhurdle(exacerbations ~ crp, data = copd,
                     index = c("id", "visit"))
#> 26 group(s) with no within-group outcome variation dropped (all-0 or all-1) -- they carry no information for the conditional likelihood.
#> 6 group(s) whose positive counts are all 1 dropped from the count part -- their intercept is not finite and they carry no information.
plot(fit)

plot(fit, which = "correlation")