bnecfit as fitted by function bnec.R/bnecfit-methods.R
update.bnecfit.Rd# S3 method for class 'bnecfit'
update(
object,
newdata = NULL,
recompile = NULL,
x_range = NA,
resolution = 1000,
sig_val = 0.01,
loo_controls,
force_fit = FALSE,
...
)Optional data.frame to update the model
with new data. Data-dependent default priors will not be updated
automatically.
A logical, indicating whether the Stan
model should be recompiled. If NULL (the default), update
tries to figure out internally, if recompilation is necessary. Setting it to
FALSE will cause all Stan code changing arguments to be ignored.
A range of predictor values over which to consider extracting ECx.
The length of the predictor vector used for posterior predictions, and over which to extract ECx values. Large values will be slower but more precise.
Probability value to use as the lower quantile to test significance of the predicted posterior values against the lowest observed concentration (assumed to be the control), to estimate NEC as an interpolated NOEC value from smooth ECx curves.
A named list of two elements
("fitting" and/or "weights"), each being a named list
containing the desired arguments to be passed on to loo
(via "fitting") or to loo_model_weights (via "weights").
If "weights" is
not provided by the user, bnec will set the default
method argument in loo_model_weights to
"pseudobma". See ?loo_model_weights for further info.
Should model truly be updated in case either
newdata of a new family is provided?
Further arguments to brm.
An object of class bnecfit. If one single model is
returned, then also an object of class bayesnecfit; otherwise,
if multiple models are returned, also an object of class
bayesmanecfit.
if (FALSE) { # \dontrun{
library(bayesnec)
data(manec_example)
# due to package size issues, `manec_example` does not contain original
# stanfit DSO, so need to recompile here
smaller_manec <- update(manec_example, chains = 2, iter = 50,
recompile = TRUE)
# original `manec_example` is fit with a Gaussian
# change to Beta distribution by adding newdata with original `nec_data$y`
# function will throw informative message.
beta_manec <- update(manec_example, newdata = nec_data, recompile = TRUE,
chains = 2, iter = 50,
family = Beta(link = "identity"), force_fit = TRUE)
} # }