Summary method for discharge rating curves

Summarize a discharge rating curve model object

Usage

# S3 method for class 'plm0'
summary(object, ...)

# S3 method for class 'plm'
summary(object, ...)

# S3 method for class 'gplm0'
summary(object, ...)

# S3 method for class 'gplm'
summary(object, ...)

Arguments

object

an object of class "plm0", "plm", "gplm0" or "gplm".

...

Not used in this function

Functions

• summary(plm0): Summary method for plm0

• summary(plm): Summary method for plm

• summary(gplm0): Summary method for gplm0

• summary(gplm): Summary method for gplm

See also

plm0, plm, gplm0 and gplm for fitting a discharge rating curve. It is also useful to look at plot.plm0, plot.plm, plot.gplm0 and plot.gplm to help visualize all aspects of the fitted discharge rating curve. Additionally, spread_draws and spread_draws help working directly with the MCMC samples.

Examples

# \donttest{
data(krokfors)
set.seed(1)
plm0.fit <- plm0(formula=Q~W,data=krokfors,num_cores=2)
#> Progress:
#> Initializing Metropolis MCMC algorithm...
#> Multiprocess sampling (4 chains in 2 jobs) ...
#> 
#> MCMC sampling completed!
#> 
#> Diagnostics:
#> Acceptance rate: 36.09%.
#> ✔ All chains have mixed well (Rhat < 1.1).
#> ✔ Effective sample sizes sufficient (eff_n_samples > 400).
summary(plm0.fit)
#> 
#> Formula: 
#>  Q ~ W
#> Latent parameters:
#>   lower-2.5% median-50% upper-97.5%
#> a 1.15       1.64       2.12       
#> b 2.46       2.82       3.21       
#> 
#> Hyperparameters:
#>           lower-2.5% median-50% upper-97.5%
#> c         7.580      7.676      7.752      
#> sigma_eps 0.151      0.191      0.253      
#> 
#> WAIC: -2.864096
# }