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Calibrate a bayesian model to fit log(AGBD) ~ log(raster metric)

Source: R/calibrate_model.R
calibrate_model.Rd

After applying the subplot_summary() function, this function fits a log-log bayesian regression model with spatially varying coefficient process, on AGBD and raster metric simulated values (see Details).

Usage

calibrate_model(
  long_AGB_simu,
  nb_rep = 30,
  useCache = FALSE,
  plot_model = TRUE,
  chains = 4,
  thin = 20,
  iter = 2300,
  warmup = 300,
  cores = 4,
  ...
)

Arguments

long_AGB_simu

The '$long_AGB_simu' output of the subplot_summary() function (see Details).

nb_rep

Number of simulation to provide in the brms fit (nb_rep > 50 will not improved significantly the model and will be much longer to fit).

useCache

A logical that determines wether to use the cache when building a Bayesian model (see Details).

plot_model

A logical indicating whether the model should be plot.

chains

Number of Markov chains (defaults to 3), see brms::brm()

thin

Thinning rate, see brms::brm()

iter

Number of total iterations per chain (including warmup; defaults to 5000), see brms::brm()

warmup

Number of warmup (aka burnin) iterations (defaults to 1000), see brms::brm()

cores

Number of cores to use when executing the chains in parallel, see brms::brm()

...

Further arguments passed to brm(), e.g: prior, cores, etc. See brms::brm()

Value

The function return a brmsfit object.

Details

The 'long_AGB_simu' argument must be a data frame or data frame extension containing the following variables:

  • 'N_simu': a numeric indicating the simulation number.

  • 'x_center' and 'y_center': the coordinates of the plots/subplots in the projected coordinate system.

  • 'AGBD': the AGBD value of the simulation.

  • 'raster_metric': the raster metric value of the simulation.

Speak about the model (fixed intercept), capturing the spatial autocorrelation, and cite Gelfand et al. 2003 (Spatial modeling with spatially varying coefficient processes)

If useCache = TRUE and this is the first time the model is being built, the model will be saved as a .rds file in the defined cache path (see createCache()). If useCache = TRUE and the model has already been built using the user cache, the model will be loaded and updated to avoid wasting time re-compiling it. If useCache = NULL, the cache is first cleared before building the model.

Author

Arthur BAILLY, Dominique LAMONICA

Examples

if (FALSE) { # \dontrun{

} # }