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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 0.590 -1.09   0.000835 0.299 0.590
#>  2 1              2 2.38  -0.753  0.00981  0.807 2.38 
#>  3 1              3 0.906 -0.413  0.0604   0.460 0.906
#>  4 1              4 1.72  -0.0725 0.205    0.706 1.72 
#>  5 1              5 3.94   0.268  0.404    0.915 3.94 
#>  6 1              6 0.697  0.608  0.494    0.359 0.697
#>  7 1              7 0.981  0.949  0.412    0.492 0.981
#>  8 1              8 1.46   1.29   0.304    0.647 1.46 
#>  9 1              9 2.62   1.63   0.264    0.832 2.62 
#> 10 1             10 1.09   1.97   0.230    0.535 1.09 
#> # … with 40 more rows