plot.plm0 {bdrc} | R Documentation |
Plot method for discharge rating curves
Description
Visualize discharge rating curve model objects
Usage
## S3 method for class 'plm0'
plot(
x,
...,
type = "rating_curve",
param = NULL,
transformed = FALSE,
title = NULL,
xlim = NULL,
ylim = NULL
)
## S3 method for class 'plm'
plot(
x,
...,
type = "rating_curve",
param = NULL,
transformed = FALSE,
title = NULL,
xlim = NULL,
ylim = NULL
)
## S3 method for class 'gplm0'
plot(
x,
...,
type = "rating_curve",
param = NULL,
transformed = FALSE,
title = NULL,
xlim = NULL,
ylim = NULL
)
## S3 method for class 'gplm'
plot(
x,
...,
type = "rating_curve",
param = NULL,
transformed = FALSE,
title = NULL,
xlim = NULL,
ylim = NULL
)
Arguments
x |
object of class "plm0", "plm", "gplm0" or "gplm". |
... |
other plotting parameters (not used in this function) |
type |
a character denoting what type of plot should be drawn. Defaults to "rating_curve". Possible types are
|
param |
a character vector with the parameters to plot. Defaults to NULL and is only used if type is "trace" or "histogram". Allowed values are the parameters given in the model summary of x as well as "hyperparameters" or "latent_parameters" for specific groups of parameters. |
transformed |
a logical value indicating whether the quantity should be plotted on a transformed scale used during the Bayesian inference. Defaults to FALSE. |
title |
a character denoting the title of the plot |
xlim |
numeric vector of length 2, denoting the limits on the x axis of the plot. Applicable for types "rating_curve","rating_curve_mean","f","beta","sigma_eps","residuals". |
ylim |
numeric vector of length 2, denoting the limits on the y axis of the plot. Applicable for types "rating_curve","rating_curve_mean","f","beta","sigma_eps","residuals". |
Value
No return value, called for side effects.
Functions
-
plot(plm0)
: Plot method for plm0 -
plot(plm)
: Plot method for plm -
plot(gplm0)
: Plot method for gplm0 -
plot(gplm)
: Plot method for gplm
See Also
plm0
, plm
, gplm0
and gplm
for fitting a discharge rating curve and summary.plm0
, summary.plm
, summary.gplm0
and summary.gplm
for summaries. It is also useful to look at spread_draws
and gather_draws
to work directly with the MCMC samples.
Examples
data(krokfors)
set.seed(1)
plm0.fit <- plm0(formula=Q~W,data=krokfors,num_cores=2)
plot(plm0.fit)
plot(plm0.fit,transformed=TRUE)
plot(plm0.fit,type='histogram',param='c')
plot(plm0.fit,type='histogram',param='c',transformed=TRUE)
plot(plm0.fit,type='histogram',param='hyperparameters')
plot(plm0.fit,type='histogram',param='latent_parameters')
plot(plm0.fit,type='residuals')
plot(plm0.fit,type='f')
plot(plm0.fit,type='sigma_eps')