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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 0.210 -1.42   0.000994 0.0594 0.210
#>  2 1              2 1.48  -1.22   0.00319  0.652  1.48 
#>  3 1              3 0.278 -1.03   0.00893  0.100  0.278
#>  4 1              4 2.13  -0.831  0.0218   0.775  2.13 
#>  5 1              5 1.29  -0.635  0.0465   0.600  1.29 
#>  6 1              6 2.08  -0.439  0.0872   0.768  2.08 
#>  7 1              7 0.414 -0.243  0.144    0.189  0.414
#>  8 1              8 1.73  -0.0473 0.211    0.708  1.73 
#>  9 1              9 1.43   0.149  0.275    0.641  1.43 
#> 10 1             10 2.36   0.345  0.325    0.804  2.36 
#> # ℹ 40 more rows