Tidy Randomly Generated Exponential Distribution Tibble — tidy_exponential • TidyDensity
Description: This function will generate n random points from a exponential distribution with a user provided, .rate, 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 Exponential Distribution Tibble

Source: `R/random-tidy-exponential.R`
`tidy_exponential.Rd`

This function will generate `n` random points from a exponential distribution with a user provided, `.rate`, 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_exponential(.n = 50, .rate = 1, .num_sims = 1)

## Arguments

.n

  The number of randomly generated points you want.

.rate

  A vector of rates

.num_sims

  The number of randomly generated simulations you want.

## Value

A tibble of randomly generated data.

## Details

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

## See also

https://www.itl.nist.gov/div898/handbook/eda/section3/eda3667.htm

Other Continuous Distribution: `tidy_beta()`, `tidy_burr()`, `tidy_cauchy()`, `tidy_chisquare()`, `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_pareto1()`, `tidy_pareto()`, `tidy_t()`, `tidy_uniform()`, `tidy_weibull()`, `tidy_zero_truncated_geometric()`

Other Exponential: `tidy_inverse_exponential()`, `util_exponential_param_estimate()`, `util_exponential_stats_tbl()`

## Author

Steven P. Sanderson II, MPH

## Examples

    tidy_exponential()
    #> # A tibble: 50 × 7
    #>    sim_number     x      y       dx       dy      p      q
    #>    <fct>      <int>  <dbl>    <dbl>    <dbl>  <dbl>  <dbl>
    #>  1 1              1 1.05   -0.930   0.000941 0.651  1.05
    #>  2 1              2 0.483  -0.775   0.00412  0.383  0.483
    #>  3 1              3 2.42   -0.621   0.0146   0.911  2.42
    #>  4 1              4 1.08   -0.466   0.0423   0.659  1.08
    #>  5 1              5 1.71   -0.312   0.101    0.819  1.71
    #>  6 1              6 0.348  -0.157   0.200    0.294  0.348
    #>  7 1              7 0.421  -0.00282 0.333    0.343  0.421
    #>  8 1              8 1.17    0.152   0.470    0.688  1.17
    #>  9 1              9 0.821   0.306   0.568    0.560  0.821
    #> 10 1             10 0.0645  0.461   0.596    0.0625 0.0645
    #> # ℹ 40 more rows