
Estimate Zero-Truncated Geometric Parameters
Source:R/est-param-zt-geometric.R
util_zero_truncated_geometric_param_estimate.RdThis function will estimate the prob parameter for a
Zero-Truncated Geometric distribution from a given vector .x. The function
returns a list with a parameter table, and if .auto_gen_empirical is set
to TRUE, the empirical data is combined with the estimated distribution
data.
Arguments
- .x
The vector of data to be passed to the function. Must contain non-negative integers and should have no zeros.
- .auto_gen_empirical
Boolean value (default
TRUE) that, when set toTRUE, will generatetidy_empirical()output for.xand combine it with the estimated distribution data.
Details
This function will attempt to estimate the prob parameter of the
Zero-Truncated Geometric distribution using given vector .x as input data.
If the parameter .auto_gen_empirical is set to TRUE, the empirical data
in .x will be run through the tidy_empirical() function and combined with
the estimated zero-truncated geometric data.
See also
Other Parameter Estimation:
util_bernoulli_param_estimate(),
util_beta_param_estimate(),
util_binomial_param_estimate(),
util_burr_param_estimate(),
util_cauchy_param_estimate(),
util_chisquare_param_estimate(),
util_exponential_param_estimate(),
util_f_param_estimate(),
util_gamma_param_estimate(),
util_generalized_beta_param_estimate(),
util_generalized_pareto_param_estimate(),
util_geometric_param_estimate(),
util_hypergeometric_param_estimate(),
util_inverse_burr_param_estimate(),
util_inverse_pareto_param_estimate(),
util_inverse_weibull_param_estimate(),
util_logistic_param_estimate(),
util_lognormal_param_estimate(),
util_negative_binomial_param_estimate(),
util_normal_param_estimate(),
util_paralogistic_param_estimate(),
util_pareto1_param_estimate(),
util_pareto_param_estimate(),
util_poisson_param_estimate(),
util_t_param_estimate(),
util_triangular_param_estimate(),
util_uniform_param_estimate(),
util_weibull_param_estimate(),
util_zero_truncated_binomial_param_estimate(),
util_zero_truncated_negative_binomial_param_estimate(),
util_zero_truncated_poisson_param_estimate()
Other Zero-Truncated Geometric:
util_zero_truncated_geometric_stats_tbl()
Examples
library(actuar)
library(dplyr)
library(ggplot2)
library(actuar)
set.seed(123)
ztg <- rztgeom(100, prob = 0.2)
output <- util_zero_truncated_geometric_param_estimate(ztg)
output$parameter_tbl
#> # A tibble: 1 × 9
#> dist_type samp_size min max mean variance sum_x method prob
#> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <dbl>
#> 1 Zero-Truncated Geomet… 100 1 16 4.78 13.5 478 Momen… 0.209
output$combined_data_tbl |>
tidy_combined_autoplot()