View source: R/est-param-geometric.R
| util_geometric_param_estimate | R Documentation |
This function will attempt to estimate the geometric prob parameter
given some vector of values .x. The function will return a list output by default, and if the parameter
.auto_gen_empirical is set to TRUE then the empirical data given to the
parameter .x will be run through the tidy_empirical() function and combined
with the estimated geometric data.
util_geometric_param_estimate(.x, .auto_gen_empirical = TRUE)
.x |
The vector of data to be passed to the function. Must be non-negative integers. |
.auto_gen_empirical |
This is a boolean value of TRUE/FALSE with default
set to TRUE. This will automatically create the |
This function will see if the given vector .x is a numeric vector.
It will attempt to estimate the prob parameter of a geometric distribution.
A tibble/list
Steven P. Sanderson II, MPH
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_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_geometric_param_estimate(),
util_zero_truncated_negative_binomial_param_estimate(),
util_zero_truncated_poisson_param_estimate()
Other Geometric:
tidy_geometric(),
tidy_zero_truncated_geometric(),
util_geometric_stats_tbl()
library(dplyr)
library(ggplot2)
tg <- tidy_geometric(.prob = .1) |> pull(y)
output <- util_geometric_param_estimate(tg)
output$parameter_tbl
output$combined_data_tbl |>
tidy_combined_autoplot()
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