View source: R/goodness_of_fit.R
LLK_GOF | R Documentation |
A function to estimate log likelihood (LLK) goodness-of-fit
LLK_GOF(
.samples,
.func,
.args = list(NULL),
.l_targets,
.maximise = TRUE,
.optim = FALSE,
...
)
.samples |
A table or vector of sampled parameter values |
.func |
A function defining the model to be calibrated |
.args |
A list of arguments to be passed to .func |
.l_targets |
A list containing a vector of targets' names, a vector of targets' weights, a vector of targets' distributions, and a table for each target that contains the values (column name 'value') and standard errors (column name 'sd') of the corresponding target. |
.maximise |
Logical for whether the output of the function is used
in a maximising optimisation function. Default is |
.optim |
Logical for whether the function is used by an
optimisation algorithm. Default is |
... |
Extra arguments, e.g. seed number and vector of calibrated parameters' names or .sample_method (for labelling purposes). |
A table with proposed parameter sets and their corresponding summed overall likelihood values sorted in descending order.
## Not run:
library(calibR)
data("CRS_targets")
Surv <- CRS_targets$Surv
v_targets_names <- c("Surv")
v_targets_dists <- c('norm')
v_targets_weights <- c(1)
l_targets <- list('v_targets_names' = v_targets_names, 'Surv' = Surv,
'v_targets_dists' = v_targets_dists,
'v_targets_weights' = v_targets_weights)
v_params_names <- c("p_Mets", "p_DieMets")
v_params_dists <- c("unif", "unif")
args <- list(list(min = 0.04, max = 0.16),
list(min = 0.04, max = 0.12))
l_params = list(v_params_names = v_params_names,
v_params_dists = v_params_dists,
args = args)
samples <- sample_prior_LHS(.l_params = l_params,
.n_samples = 10)
GOF_llik <- LLK_GOF(.func = CRS_markov, .samples = samples,
.l_targets = l_targets)
## End(Not run)
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