| plot_diagnostic | R Documentation |
plot_diagnostic creates visual MCMC diagnostics for a
fitted brma object. Convenience wrappers are available for trace, density,
and autocorrelation plots.
plot_diagnostic(x, ...)
## S3 method for class 'brma'
plot_diagnostic(
x,
parameter = NULL,
parameter_mods = NULL,
parameter_scale = NULL,
type,
plot_type = "base",
lags = 30,
...
)
plot_diagnostic_autocorrelation(x, ...)
## S3 method for class 'brma'
plot_diagnostic_autocorrelation(
x,
parameter = NULL,
parameter_mods = NULL,
parameter_scale = NULL,
type = "autocorrelation",
plot_type = "base",
lags = 30,
...
)
plot_diagnostic_trace(x, ...)
## S3 method for class 'brma'
plot_diagnostic_trace(
x,
parameter = NULL,
parameter_mods = NULL,
parameter_scale = NULL,
type = "trace",
plot_type = "base",
lags = 30,
...
)
plot_diagnostic_density(x, ...)
## S3 method for class 'brma'
plot_diagnostic_density(
x,
parameter = NULL,
parameter_mods = NULL,
parameter_scale = NULL,
type = "density",
plot_type = "base",
lags = 30,
...
)
x |
a fitted brma object |
... |
additional graphical arguments passed through RoBMA's diagnostic
setup to |
parameter |
base parameter to plot. Defaults to |
parameter_mods |
moderator term for location regression. |
parameter_scale |
term for scale regression. |
type |
diagnostic plot type. Convenience wrappers set a type-specific
default but still forward this argument to |
plot_type |
whether to use a base plot |
lags |
number of lags for autocorrelation plots. Defaults to 30. |
plot_diagnostic returns the object returned by
BayesTools::JAGS_diagnostics(), invisibly for base graphics.
summary.brma()
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