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Calculate Akaike Information Criterion (AIC) for F Distribution
Source:R/utils-aic-f.R
util_f_aic.Rd
This function estimates the parameters of a F distribution from the provided data using maximum likelihood estimation, and then calculates the AIC value based on the fitted distribution.
Details
This function calculates the Akaike Information Criterion (AIC) for an F distribution fitted to the provided data.
This function fits an F distribution to the input data using maximum likelihood estimation and then computes the Akaike Information Criterion (AIC) based on the fitted distribution.
See also
rf
for generating F-distributed data,
optim
for optimization.
Other Utility:
check_duplicate_rows()
,
convert_to_ts()
,
quantile_normalize()
,
tidy_mcmc_sampling()
,
util_beta_aic()
,
util_binomial_aic()
,
util_cauchy_aic()
,
util_chisq_aic()
,
util_exponential_aic()
,
util_gamma_aic()
,
util_generalized_beta_aic()
,
util_generalized_pareto_aic()
,
util_geometric_aic()
,
util_hypergeometric_aic()
,
util_inverse_burr_aic()
,
util_inverse_pareto_aic()
,
util_inverse_weibull_aic()
,
util_logistic_aic()
,
util_lognormal_aic()
,
util_negative_binomial_aic()
,
util_normal_aic()
,
util_paralogistic_aic()
,
util_pareto1_aic()
,
util_pareto_aic()
,
util_poisson_aic()
,
util_t_aic()
,
util_triangular_aic()
,
util_uniform_aic()
,
util_weibull_aic()
,
util_zero_truncated_binomial_aic()
,
util_zero_truncated_geometric_aic()
,
util_zero_truncated_negative_binomial_aic()
,
util_zero_truncated_poisson_aic()