calc_aic: Calculates Akaike's information criterion for a maximum...
In joshwlambert/relaxedDAISIE: Reproduce Relaxed-rate DAISIE Paper
calc_aic R Documentation
Calculates Akaike's information criterion for a maximum likelihood output
of the DAISIE model
Description
Calculates Akaike's information criterion for a maximum likelihood output
of the DAISIE model
Usage
calc_aic(results, daisie_data)
Arguments
results
The maximum likelihood parameter estimates and associated log
likelihood and free parameters (degrees of freedom)
daisie_data
The data the DAISIE model was fit to
Value
A numeric
Examples
data("Comoros")
best_model <- choose_best_model(data_name = "Comoros", model = "cr_dd")
calc_aic(results = best_model, daisie_data = Comoros)
joshwlambert/relaxedDAISIE documentation built on Nov. 23, 2023, 12:29 p.m.
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| calc_aic | R Documentation |
Calculates Akaike's information criterion for a maximum likelihood output of the DAISIE model
Description
Calculates Akaike's information criterion for a maximum likelihood output of the DAISIE model
Usage
calc_aic(results, daisie_data)
Arguments
results |
The maximum likelihood parameter estimates and associated log likelihood and free parameters (degrees of freedom) |
daisie_data |
The data the DAISIE model was fit to |
Value
A numeric
Examples
data("Comoros")
best_model <- choose_best_model(data_name = "Comoros", model = "cr_dd")
calc_aic(results = best_model, daisie_data = Comoros)
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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