Description Usage Arguments Details Value Author(s) Examples
View source: R/log_likelihood.R
Noise is assumed to be independent for each entry. The default likelihood assumes the same heteroscedastic noise as the model used in add_noise
.
1 | log_likelihood(simu, simu_subset, data, fit = F)
|
simu |
Simulated time courses. |
simu_subset |
Subset of the simulated time course which relates to observed data. |
data |
Observed data. |
fit |
Should smoothness prior information about simulation added to the prior or not? |
The noise model is gaussian with variance of the form (0.01 + 0.04 * m^2)
where m
is the mean.
A numerical value.
Edouard Pauwels
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | data(experiment_list1)
data(observables)
## Generate the knowledge object with correct parameter value
knobj <- generate_our_knowledge(transform_params)
simu <- simulate_experiment(knobj$global_parameters$true_params_T, knobj, experiment_list1$nothing)
simu_subset <- simu[
knobj$global_parameters$tspan %in% observables[["mrnaLow"]]$reso,
observables[["mrnaLow"]]$obs
]
data <- add_noise(simu_subset)
log_likelihood(simu, simu_subset, data)
|
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