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This function will generate n random points from a lognormal distribution with a user provided, .meanlog, .sdlog, 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_lognormal(.n = 50, .meanlog = 0, .sdlog = 1, .num_sims = 1)

Arguments

.n

The number of randomly generated points you want.

.meanlog

Mean of the distribution on the log scale with default 0

.sdlog

Standard deviation of the distribution on the log scale with default 1

.num_sims

The number of randomly generated simulations you want.

Value

A tibble of randomly generated data.

Details

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

Author

Steven P. Sanderson II, MPH

Examples

tidy_lognormal()
#> # A tibble: 50 × 7
#>    sim_number     x     y     dx       dy      p     q
#>    <fct>      <int> <dbl>  <dbl>    <dbl>  <dbl> <dbl>
#>  1 1              1 1.06  -1.58  0.000877 0.522  1.06 
#>  2 1              2 3.08  -1.23  0.00545  0.870  3.08 
#>  3 1              3 1.50  -0.884 0.0241   0.658  1.50 
#>  4 1              4 0.722 -0.537 0.0767   0.373  0.722
#>  5 1              5 0.835 -0.190 0.177    0.429  0.835
#>  6 1              6 0.557  0.158 0.302    0.279  0.557
#>  7 1              7 0.176  0.505 0.386    0.0412 0.176
#>  8 1              8 1.11   0.852 0.385    0.542  1.11 
#>  9 1              9 3.27   1.20  0.312    0.882  3.27 
#> 10 1             10 0.267  1.55  0.221    0.0935 0.267
#> # ℹ 40 more rows