Provide two type of plots for unitquantregs
objects.
Usage
# S3 method for unitquantregs
plot(
x,
which = c("coef", "conddist"),
output_df = FALSE,
parm = NULL,
level = 0.95,
mean_effect = FALSE,
mfrow = NULL,
mar = NULL,
ylim = NULL,
main = NULL,
col = gray(c(0, 0.75)),
border = NULL,
cex = 1,
pch = 20,
type = "b",
xlab = bquote("Quantile level (" * tau * ")"),
ylab = "Estimate effect",
dist_type = c("density", "cdf"),
at_avg = TRUE,
at_obs = NULL,
legend_position = "topleft",
...
)
Arguments
- x
fitted model object of class
unitquantregs
.- which
character. Indicate the type of plot. Currently supported are
"coef"
which provide the estimated coefficients for several quantiles and"conddist"
which provide the conditional distribution (cdf or pdf) at specific values of covariates.- output_df
logical. Should
data.frame
used to plot be returned?- parm
a specification of which parameters are to be plotted, either a vector of numbers or a vector of names. By default, all parameters are considered.
- level
level of significance for the confidence interval of parameters.
- mean_effect
logical. Should a line for the mean effect coefficients be added?
- mfrow, mar, ylim, main, col, border, cex, pch, type, xlab, ylab
graphical parameters.
- dist_type
character. Which conditional distribution should be plotted? The options are
"density"
or"cdf"
.- at_avg
logical. Should consider the conditional distribution at average values of covariates?
- at_obs
list. List with name and values for each covariate.
- legend_position
character. The legend position argument used in
legend
function.- ...
other parameters to be passed through to plotting functions.
Value
If output_df = TRUE
then returns a data.frame used to plot.
Otherwise, no return value, called for side effects.
Details
The plot method for unitquantregs
objects is inspired in PROC QUANTREG of SAS/STAT.
This plot method provide two type of visualizations.
If which = "coef"
plot the estimated coefficients for several quantiles.
If which = "conddist"
plot the conditional distribution at specific values of
covariates. The conditional distribution could be the cumulative distribution function
if dist_type = "cdf"
or the probability density function if dist_type = "pdf"
.