Gather MCMC chain draws to data.frame on a long format

Useful to convert MCMC chain draws of particular parameters or output from the model object to a long format for further data wrangling

Usage

gather_draws(mod, ..., transformed = F)

Arguments

mod: An object of class "plm0", "plm", "gplm0" or "gplm".
...: Any number of character vectors containing valid names of parameters in the model or "rating_curve" and "rating_curve_mean". Also accepts "latent_parameters" and "hyperparameters".
transformed: A boolean value determining whether the parameter is to be represented on the transformed scale used for sampling in the MCMC chain or the original scale. Defaults to FALSE.

Value

A data frame with columns:

chain: The chain number.
iter: The iteration number.
param: The parameter name.
value: The parameter value.

References

Hrafnkelsson, B., Sigurdarson, H., Rögnvaldsson, S., Jansson, A. Ö., Vias, R. D., and Gardarsson, S. M. (2022). Generalization of the power-law rating curve using hydrodynamic theory and Bayesian hierarchical modeling, Environmetrics, 33(2):e2711. doi: https://doi.org/10.1002/env.2711

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).
 hyp_samples <- gather_draws(plm0.fit,'hyperparameters')
 head(hyp_samples)
#>   chain iter name    value
#> 1     1    1    c 7.693275
#> 2     1    2    c 7.708797
#> 3     1    3    c 7.704167
#> 4     1    4    c 7.666575
#> 5     1    5    c 7.658464
#> 6     1    6    c 7.709366
 rating_curve_samples <- gather_draws(plm0.fit,'rating_curve','rating_curve_mean')
 head(rating_curve_samples)
#>   chain iter        h         name        value
#> 1     1    1 7.673811 rating_curve 0.000000e+00
#> 2     1    2 7.673811 rating_curve 0.000000e+00
#> 3     1    3 7.673811 rating_curve 0.000000e+00
#> 4     1    4 7.673811 rating_curve 1.094841e-06
#> 5     1    5 7.673811 rating_curve 6.537614e-06
#> 6     1    6 7.673811 rating_curve 0.000000e+00
# }