Tidy Randomly Generated Pareto Single Parameter Distribution Tibble — tidy_pareto1 • TidyDensity
Description: This function will generate n random points from a single parameter pareto distribution with a user provided, .shape, .min, and number of random simulations to be produced. The function returns a tibble with the simulation number column the x column which corresponds to the n randomly generated points, the d_, p_ and q_ data points as well. The data is returned un-grouped. The columns that are output are: sim_number The current simulation number. x The current value of n for the current simulation. y The randomly generated data point. dx The x value from the stats::density() function. dy The y value from the stats::density() function. p The values from the resulting p_ function of the distribution family. q The values from the resulting q_ function of the distribution family.

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# Tidy Randomly Generated Pareto Single Parameter Distribution Tibble

Source: `R/random-tidy-pareto-single-param.R`
`tidy_pareto1.Rd`

This function will generate `n` random points from a single parameter pareto distribution with a user provided, `.shape`, `.min`, and number of random simulations to be produced. The function returns a tibble with the simulation number column the x column which corresponds to the n randomly generated points, the `d_`, `p_` and `q_` data points as well.

The data is returned un-grouped.

The columns that are output are:

- `sim_number` The current simulation number.

- `x` The current value of `n` for the current simulation.

- `y` The randomly generated data point.

- `dx` The `x` value from the `stats::density()` function.

- `dy` The `y` value from the `stats::density()` function.

- `p` The values from the resulting p_ function of the distribution family.

- `q` The values from the resulting q_ function of the distribution family.

## Usage

    tidy_pareto1(.n = 50, .shape = 1, .min = 1, .num_sims = 1)

## Arguments

.n

  The number of randomly generated points you want.

.shape

  Must be positive.

.min

  The lower bound of the support of the distribution.

.num_sims

  The number of randomly generated simulations you want.

## Value

A tibble of randomly generated data.

## Details

This function uses the underlying `actuar::rpareto1()`, and its underlying `p`, `d`, and `q` functions. For more information please see `actuar::rpareto1()`

## See also

https://openacttexts.github.io/Loss-Data-Analytics/ChapSummaryDistributions.html

Other Continuous Distribution: `tidy_beta()`, `tidy_burr()`, `tidy_cauchy()`, `tidy_chisquare()`, `tidy_exponential()`, `tidy_f()`, `tidy_gamma()`, `tidy_generalized_beta()`, `tidy_generalized_pareto()`, `tidy_geometric()`, `tidy_inverse_burr()`, `tidy_inverse_exponential()`, `tidy_inverse_gamma()`, `tidy_inverse_normal()`, `tidy_inverse_pareto()`, `tidy_inverse_weibull()`, `tidy_logistic()`, `tidy_lognormal()`, `tidy_normal()`, `tidy_paralogistic()`, `tidy_pareto()`, `tidy_t()`, `tidy_uniform()`, `tidy_weibull()`, `tidy_zero_truncated_geometric()`

Other Pareto: `tidy_generalized_pareto()`, `tidy_inverse_pareto()`, `tidy_pareto()`, `util_pareto_param_estimate()`, `util_pareto_stats_tbl()`

## Author

Steven P. Sanderson II, MPH

## Examples

    tidy_pareto1()
    #> # A tibble: 50 × 7
    #>    sim_number     x     y      dx      dy      p     q
    #>    <fct>      <int> <dbl>   <dbl>   <dbl>  <dbl> <dbl>
    #>  1 1              1  3.69 -1.19   0.00133 0.729   3.69
    #>  2 1              2  1.57 -0.772  0.00694 0.361   1.57
    #>  3 1              3  1.06 -0.350  0.0264  0.0593  1.06
    #>  4 1              4  1.27  0.0717 0.0741  0.211   1.27
    #>  5 1              5  4.02  0.494  0.155   0.751   4.02
    #>  6 1              6  1.80  0.916  0.246   0.445   1.80
    #>  7 1              7  1.06  1.34   0.303   0.0528  1.06
    #>  8 1              8  1.11  1.76   0.299   0.100   1.11
    #>  9 1              9 10.9   2.18   0.247   0.908  10.9
    #> 10 1             10  1.02  2.60   0.183   0.0152  1.02
    #> # ℹ 40 more rows