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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 0.450 -1.21  0.00168 0.212  0.450
#>  2 1              2 0.414 -0.938 0.00936 0.189  0.414
#>  3 1              3 3.76  -0.668 0.0380  0.907  3.76 
#>  4 1              4 0.749 -0.398 0.113   0.386  0.749
#>  5 1              5 1.27  -0.128 0.246   0.594  1.27 
#>  6 1              6 0.196  0.142 0.398   0.0517 0.196
#>  7 1              7 0.895  0.412 0.489   0.456  0.895
#>  8 1              8 1.15   0.681 0.469   0.556  1.15 
#>  9 1              9 0.977  0.951 0.373   0.491  0.977
#> 10 1             10 0.569  1.22  0.276   0.286  0.569
#> # ℹ 40 more rows