util_zero_truncated_poisson_aic {TidyDensity} | R Documentation |
Calculate Akaike Information Criterion (AIC) for zero-truncated poisson Distribution
Description
This function estimates the parameters of a zero-truncated poisson distribution from the provided data using maximum likelihood estimation, and then calculates the AIC value based on the fitted distribution.
Usage
util_zero_truncated_poisson_aic(.x)
Arguments
.x |
A numeric vector containing the data to be fitted to a zero-truncated poisson distribution. |
Details
This function calculates the Akaike Information Criterion (AIC) for a zero-truncated poisson distribution fitted to the provided data.
Value
The AIC value calculated based on the fitted zero-truncated poisson distribution to the provided data.
Author(s)
Steven P. Sanderson II, MPH
See Also
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_f_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()
Examples
library(actuar)
# Example 1: Calculate AIC for a sample dataset
set.seed(123)
x <- rztpois(30, lambda = 3)
util_zero_truncated_poisson_aic(x)