bayesnec
standard ggplot2
plotting method.
# S3 method for bayesnecfit
autoplot(object, ..., nec = TRUE, ecx = FALSE, force_x = FALSE, xform = NA)
An object of class bayesnecfit
as returned by
function bnec
.
Additional arguments to be passed to ggbnec_data
.
Should NEC values be added to the plot? Defaults to TRUE.
Should ECx values be added to the plot? Defaults to FALSE.
A logical
value indicating if the argument
xform
should be forced on the predictor values. This is useful when
the user transforms the predictor beforehand
(e.g. when using a non-standard base function).
A function to apply to the returned estimated concentration values.
A ggplot
object.
Other autoplot methods:
autoplot.bayesmanecfit()
# \donttest{
library(brms)
library(bayesnec)
options(mc.cores = 2)
data(nec_data)
necs <- bnec(y ~ crf(x, c("nec3param", "nec4param")), data = nec_data,
iter = 2e2, family = Beta(link = "identity"))
#> Finding initial values which allow the response to be fitted using a nec3param model and a beta distribution.
#> Compiling Stan program...
#> Start sampling
#> Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#bulk-ess
#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#tail-ess
#> Response variable modelled as a nec3param model using a beta distribution.
#> Finding initial values which allow the response to be fitted using a nec4param model and a beta distribution.
#> Compiling Stan program...
#> Start sampling
#> Warning: The largest R-hat is 1.07, indicating chains have not mixed.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#r-hat
#> Warning: Bulk Effective Samples Size (ESS) is too low, indicating posterior means and medians may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#bulk-ess
#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#tail-ess
#> Response variable modelled as a nec4param model using a beta distribution.
#> Fitted models are: nec3param nec4param
#> Warning: Found 2 observations with a pareto_k > 0.7 in model 'nec3param'. It is recommended to set 'moment_match = TRUE' in order to perform moment matching for problematic observations.
#> Warning:
#> 2 (2.0%) p_waic estimates greater than 0.4. We recommend trying loo instead.
#> Warning: Found 1 observations with a pareto_k > 0.7 in model 'nec4param'. It is recommended to set 'moment_match = TRUE' in order to perform moment matching for problematic observations.
#> Warning:
#> 3 (3.0%) p_waic estimates greater than 0.4. We recommend trying loo instead.
nec3param <- pull_out(necs, "nec3param")
#> Pulling out model(s): nec3param
autoplot(nec3param)
autoplot(nec3param, nec = FALSE)
autoplot(nec3param, ecx = TRUE, ecx_val = 50)
# plot model averaged predictions
autoplot(necs)
# plot all panels together
autoplot(necs, ecx = TRUE, ecx_val = 50, all_models = TRUE)
# plots multiple models, one at a time, with interactive prompt
autoplot(necs, ecx = TRUE, ecx_val = 50, all_models = TRUE,
multi_facet = FALSE)
# }