train_GAM: Train a Generalized Additive Model on Simulation Data
In franciscorichter/emphasis: Evolutionary Modeling on Phylogenetic Applications with Simulations and Importance Sampling
train_GAM R Documentation
Train a Generalized Additive Model on Simulation Data
Description
This function fits a Generalized Additive Model (GAM) to the provided simulation
results. It models the log-likelihood of simulation success ('loglik') as a function
of the simulation parameters, using smooth terms for each parameter. Only simulations
that completed successfully are used for the model fitting.
Usage
train_GAM(results)
Arguments
results
A list containing simulation results with the following components:
- 'loglik_estimation': A list of log-likelihood values or 'try-error' objects.
- 'trees': A list of data frames, each containing tree data.
- 'param': A list of named vectors containing the simulation parameters 'mu',
'lambda', 'betaN', and 'betaP'.
Value
A 'gam' object representing the fitted model.
Examples
# Assuming 'results' is your list of simulation results:
gam_model <- train_GAM(results)
summary(gam_model)
franciscorichter/emphasis documentation built on Feb. 19, 2024, 7:36 p.m.
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| train_GAM | R Documentation |
Train a Generalized Additive Model on Simulation Data
Description
This function fits a Generalized Additive Model (GAM) to the provided simulation results. It models the log-likelihood of simulation success ('loglik') as a function of the simulation parameters, using smooth terms for each parameter. Only simulations that completed successfully are used for the model fitting.
Usage
train_GAM(results)
Arguments
results |
A list containing simulation results with the following components: - 'loglik_estimation': A list of log-likelihood values or 'try-error' objects. - 'trees': A list of data frames, each containing tree data. - 'param': A list of named vectors containing the simulation parameters 'mu', 'lambda', 'betaN', and 'betaP'. |
Value
A 'gam' object representing the fitted model.
Examples
# Assuming 'results' is your list of simulation results:
gam_model <- train_GAM(results)
summary(gam_model)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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