Breaking Changes

1. Fix #521 - Fundamentally redesign of quantile_normalize() to use a more efficient
   algorithm. This has resulted in a breaking change as the output is now slightly
   different. The new algorithm is also faster and more memory efficient.

New Features

1. Fix #510 - Add parameter to tidy_mixture_density() to allow for different
   types of combinations, add, subtract, stack, multiply and divide.

Minor Fixes and Improvements

None

Breaking Changes

None

New Features

None

Minor Fixes and Improvements

1. Fix #515 - Fix documentation issue with rinvgauss
2. Fix #514 - Fix documentation issue with tidy_geometric()

Breaking Changes

None

New Features

1. Fix #468 - Add function util_negative_binomial_aic() to calculate the AIC for the negative binomial distribution.
2. Fix #470 - Add function util_zero_truncated_negative_binomial_param_estimate() to
   estimate the parameters of the zero-truncated negative binomial distribution.
   Add function util_zero_truncated_negative_binomial_aic() to calculate the AIC for the zero-truncated negative binomial distribution.
   Add function util_zero_truncated_negative_binomial_stats_tbl() to create a summary table of the zero-truncated negative binomial distribution.
3. Fix #471 - Add function util_zero_truncated_poisson_param_estimate() to estimate
   the parameters of the zero-truncated Poisson distribution.
   Add function util_zero_truncated_poisson_aic() to calculate the AIC for the zero-truncated Poisson distribution.
   Add function util_zero_truncated_poisson_stats_tbl() to create a summary table of the zero-truncated Poisson distribution.
4. Fix #472 - Add function util_f_param_estimate() and util_f_aic() to estimate the parameters and calculate the AIC for the F distribution.
5. Fix #482 - Add function util_zero_truncated_geometric_param_estimate() to estimate the parameters of the zero-truncated geometric distribution.
   Add function util_zero_truncated_geometric_aic() to calculate the AIC for the zero-truncated geometric distribution.
   Add function util_zero_truncated_geometric_stats_tbl() to create a summary table of the zero-truncated geometric distribution.
6. Fix #481 - Add function util_triangular_aic() to calculate the AIC for the triangular distribution.
7. Fix #480 - Add function util_t_param_estimate() to estimate the parameters of the
   T distribution.
   Add function util_t_aic() to calculate the AIC for the T distribution.
8. Fix #479 - Add function util_pareto1_param_estimate() to estimate the parameters of the Pareto Type I distribution.
   Add function util_pareto1_aic() to calculate the AIC for the Pareto Type I distribution.
   Add function util_pareto1_stats_tbl() to create a summary table of the Pareto Type I distribution.
9. Fix #478 - Add function util_paralogistic_param_estimate() to estimate the parameters of the paralogistic distribution.
   Add function util_paralogistic_aic() to calculate the AIC for the paralogistic distribution.
   Add fnction util_paralogistic_stats_tbl() to create a summary table of the paralogistic distribution.
10. Fix #477 - Add function util_inverse_weibull_param_estimate() to estimate the parameters of the Inverse Weibull distribution.
    Add function util_inverse_weibull_aic() to calculate the AIC for the Inverse Weibull distribution.
    Add function util_inverse_weibull_stats_tbl() to create a summary table of the Inverse Weibull distribution.
11. Fix #476 - Add function util_inverse_pareto_param_estimate() to estimate the parameters of the Inverse Pareto distribution.
    Add function util_inverse_pareto_aic() to calculate the AIC for the Inverse Pareto distribution.
    Add Function util_inverse_pareto_stats_tbl() to create a summary table of the Inverse Pareto distribution.
12. Fix #475 - Add function util_inverse_burr_param_estimate() to estimate the parameters of the Inverse Gamma distribution.
    Add function util_inverse_burr_aic() to calculate the AIC for the Inverse Gamma distribution.
    Add function util_inverse_burr_stats_tbl() to create a summary table of the Inverse Gamma distribution.
13. Fix #474 - Add function util_generalized_pareto_param_estimate() to estimate the parameters of the Generalized Pareto distribution.
    Add function util_generalized_pareto_aic() to calculate the AIC for the Generalized Pareto distribution.
    Add function util_generalized_pareto_stats_tbl() to create a summary table of the Generalized Pareto distribution.
14. Fix #473 - Add function util_generalized_beta_param_estimate() to estimate the parameters of the Generalized Gamma distribution.
    Add function util_generalized_beta_aic() to calculate the AIC for the Generalized Gamma distribution.
    Add function util_generalized_beta_stats_tbl() to create a summary table of the Generalized Gamma distribution.
15. Fix #469 - Add function util_zero_truncated_binomial_stats_tbl() to create a summary table of the Zero Truncated binomial distribution.
    Add function util_zero_truncated_binomial_param_estimate() to estimate the parameters of the Zero Truncated binomial distribution.
    Add function util_zero_truncated_binomial_aic() to calculate the AIC for the Zero Truncated binomial distribution.

Minor Improvements and Fixes

1. Fix #468 - Update util_negative_binomial_param_estimate() to add the use of
   optim() for parameter estimation.
2. Fix #465 - Add names to columns when .return_tibble = TRUE for quantile_normalize()

Breaking Changes

None

New Features

1. Fix #405 - Add function quantile_normalization() to normalize data using quantiles.
2. Fix #409 - Add function check_duplilcate_rows() to check for duplicate rows in a data frame.
3. Fix #414 - Add function util_chisquare_param_estimate() to estimate the parameters of the chi-square distribution.
4. Fix #417 - Add function tidy_mcmc_sampling() to sample from a distribution using MCMC.
   This outputs the function sampled data and a diagnostic plot.
5. Fix #421 - Add functions util_dist_aic() functions to calculate the AIC for a distribution.

Minor Fixes and Improvements

1. Fix #401 - Update tidy_multi_single_dist() to respect the .return_tibble parameter
2. Fix #406 - Update tidy_multi_single_dist() to exclude the .return_tibble parameter
   from returning in the distribution parameters.
3. Fix #413 - Update documentation to include mcmc where applicable.
4. Fix #240 - Update tidy_distribution_comparison() to include the new AIC calculations
   from the dedicated util_dist_aic() functions.

Breaking Changes

1. Fix #350 - This has caused the function tidy_multi_single_dist() to be modified
   in that it now requires the user to pass the parameter of .return_tibbl with either
   TRUE or FALSE as it was introduced into the tidy_ distribution functions which now
   use data.table under the hood to generate data.
2. Fix #371 - Modify code to use the native |> pipe instead of the %>% which
   has caused a need to update the minimum R version to 4.1.0

New Features

1. Fix #360 - Add function tidy_triangular()
2. Fix #361 - Add function util_triangular_param_estimate()
3. Fix #362 - Add function util_triangular_stats_tbl()
4. Fix #364 - Add function triangle_plot()
5. Fix #363 - Add triangular to tidy_autoplot()

Minor Fixes and Improvements

1. Fix #372 and #373 - Update cvar() and csd() to a vectorized approach from @kokbent
   which speeds these up by over 100x
2. Fix #350 - Update all tidy_ distribution functions to generate data using data.table
   this in many instances has resulted in a speed up of 30% or more.
3. Fix #379 - Replace the use of dplyr::cur_data() as it was deprecated in
   dplyr in favor of using dplyr::pick()
4. Fix #381 - Add tidy_triangular() to all autoplot functions.
5. Fix #385 - For tidy_multi_dist_autoplot() the .plot_type = "quantile" did
   not work.
6. Fix #383 - Update all autoplot functions to use linewidth instead of size.
7. Fix #375 - Update cskewness() to take advantage of vectorization with a speedup
   of 124x faster.
8. Fix #393 - Update ckurtosis() with vectorization to improve speed by 121x per
   benchmark testing.

Breaking Changes

None

New Features

1. Fix #351 - Add function convert_to_ts() which will convert a tidy_ distribution
   into a time series in either ts format or tibble you can also have it set to
   wide or long by using .pivot_longer set to TRUE and .ret_ts set to FALSE
2. Fix #348 - Add function util_burr_stats_tbl()

Minor Fixes and Improvements

1. Fix #344 - Fix util_burr_param_estimate()

Breaking Changes

None

New Features

1. Fix #333 - Add function util_burr_param_estimate()

Minor Fixes and Improvements

1. Fix #335 - Update function tidy_distribution_comparison() to add a parameter
   of .round_to_place which allows a user to round the parameter estimates passed
   to their corresponding distribution parameters.
2. Fix #336 - Update logo name to logo.png

Breaking Changes

None

New Features

1. Fix #302 - Add function tidy_bernoulli()
2. Fix #304 - Add function util_bernoulli_param_estimate()
3. Fix #305 - Add function util_bernoulli_stats_tbl()

Minor Fixes and Improvements

1. Fix #291 - Update tidy_stat_tbl() to fix tibble output so it no longer ignores
   passed arguments and fix data.table to directly pass ... arguments.
2. Fix #295 - Drop warning message of not passing arguments when .use_data_table = TRUE
3. Fix #303 - Add tidy_bernoulli() to autoplot.
4. Fix #299 - Update tidy_stat_tbl()
5. Fix #309 - Add function for internal use to drop dependency of stringr. Function
   is dist_type_extractor() which is used for several functions in the library.
6. Fix #310 - Update combine-multi-dist to use dist_type_extractor()
7. Fix #311 - Update all util_dist_stats_tbl() functions to use dist_type_extractor()
8. Fix #316 - Update all autoplot functions for tidy_bernoulli()
9. Fix #312 - Update random walk function to use dist_type_extractor()
10. Fix #314 - Update tidy_stat_tbl() to use dist_type_extractor()
11. Fix #301 - Fix p and q calculations.

Breaking Changes

None

New Features

1. Fix #237 - Add function bootstrap_density_augment()
2. Fix #238 - Add functions bootstrap_p_vec() and bootstrap_p_augment()
3. Fix #239 - Add functions bootstrap_q_vec() and bootstrap_q_augment()
4. Fix #256 #257 #258 #260 #265 #266 #267 #268 - Add functions cmean()
chmean() cgmean() cmedian() csd() ckurtosis() cskewness() cvar()
5. Fix #250 - Add function bootstrap_stat_plot()
6. Fix #276 - Add function tidy_stat_tbl() Fix #281 adds the parameter of
   .user_data_table which is set to FALSE by default. If set to TRUE will use
   [data.table::melt()] for the underlying work speeding up the output from a
   benchmark test of regular tibble at 72 seconds to data.table. at 15 seconds.

Minor Fixes and Improvements

1. Fix #242 - Fix prop check in tidy_bootstrap()
2. Fix #247 - Add attributes to bootstrap_density_augment() output.

Breaking Changes

None

New Features

1. Fix #229 - Add tidy_normal() to list of tested distributions. Add AIC from
   a linear model for metric, and add stats::ks.test() as a metric.

Minor Fixes and Improvements

1. Fix #228 - Add ks.test to distribution comparison.
2. Fix #227 - Add AIC and normal to distribution comparison.