# Unveiling New Tools in the TidyDensity Arsenal: Distribution Parameter Wrangling

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# Introduction

Greetings, fellow data enthusiasts! Today, we’re thrilled to unveil a fresh wave of functionalities in the ever-evolving TidyDensity package. Buckle up, as we delve into the realm of distribution statistics!

This update brings a bounty of new functions that streamline the process of extracting key parameters from various probability distributions. These functions adhere to the familiar naming convention `util_distribution_name_stats_tbl()`

, making them easily discoverable within your R workflow.

Let’s meet the newcomers:

`util_zero_truncated_negative_binomial_stats_tbl()`

: Uncovers the secrets of the zero-truncated negative binomial distribution.`util_zero_truncated_poisson_stats_tbl()`

: Demystifies the zero-truncated Poisson distribution.`util_zero_truncated_geometric_stats_tbl()`

: Unveils the hidden characteristics of the zero-truncated geometric distribution.`util_pareto1_stats_tbl()`

: Extracts the essence of the Pareto Type I distribution.`util_paralogistic_stats_tbl()`

: Unlocks the mysteries of the paralogistic distribution.`util_inverse_weibull_stats_tbl()`

: Illuminates the parameters of the inverse Weibull distribution.`util_inverse_pareto_stats_tbl()`

: Provides insights into the inverse Pareto distribution.`util_inverse_burr_stats_tbl()`

: Offers a glimpse into the world of the inverse Burr distribution.`util_generalized_pareto_stats_tbl()`

: Simplifies extracting parameters from the generalized Pareto distribution.

Now, you might be wondering, “How do I put these new functions to use?” Fear not, for the answer is as easy as pie!

# Examples

Let’s explore the zero-truncated binomial distribution. Suppose we’re simulating the number of successes in 10 trials with a success probability of 0.1 (but hey, successes of zero aren’t possible in this scenario!).

library(dplyr) library(TidyDensity) # Assuming you've installed TidyDensity set.seed(123) tidy_zero_truncated_binomial(.size = 10, .prob = 0.1) |> util_zero_truncated_binomial_stats_tbl() |> glimpse()

Rows: 1 Columns: 15 $ tidy_function <chr> "tidy_zero_truncated_binomial" $ function_call <chr> "Zero Truncated Binomial c(10, 0.1)" $ distribution <chr> "Zero Truncated Binomial" $ distribution_type <chr> "discrete" $ points <dbl> 50 $ simulations <dbl> 1 $ mean <dbl> 1.58 $ mode <dbl> 1 $ range <chr> "1 to 4" $ std_dv <dbl> 0.8103917 $ coeff_var <dbl> 0.5129061 $ computed_std_skew <dbl> 1.133051 $ computed_std_kurt <dbl> 3.212143 $ ci_lo <dbl> 1 $ ci_hi <dbl> 3

This code snippet generates a dataset of zero-truncated binomial values and then utilizes the `util_zero_truncated_binomial_stats_tbl()`

function to extract a summary table containing key parameters like the mean, variance, and quantiles.

# Your Turn to Explore!

We encourage you to jump in and experiment with these new additions. Explore the documentation for each function (accessible through `?util_distribution_name_stats_tbl`

) to discover their specific functionalities and supported distributions.

With these new tools at your disposal, you’ll be well-equipped to gain deeper insights into your data and unlock the power of various probability distributions in your R adventures!

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