Tidy Randomly Generated Gaussian Distribution Tibble

This function will generate n random points from a Gaussian distribution with a user provided, .mean, .sd - standard deviation 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 dnorm, pnorm and qnorm 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_normal(.n = 50, .mean = 0, .sd = 1, .num_sims = 1, .return_tibble = TRUE)

Arguments

.n: The number of randomly generated points you want.
.mean: The mean of the randomly generated data.
.sd: The standard deviation of the randomly generated data.
.num_sims: The number of randomly generated simulations you want.
.return_tibble: A logical value indicating whether to return the result as a tibble. Default is TRUE.

Value

A tibble of randomly generated data.

Details

This function uses the underlying stats::rnorm(), stats::pnorm(), and stats::qnorm() functions to generate data from the given parameters. For more information please see stats::rnorm()

Other Continuous Distribution: tidy_beta(), tidy_burr(), tidy_cauchy(), tidy_chisquare(), tidy_exponential(), 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_paralogistic(), tidy_pareto(), tidy_pareto1(), tidy_t(), tidy_triangular(), tidy_uniform(), tidy_weibull(), tidy_zero_truncated_geometric()

Other Gaussian: tidy_inverse_normal(), util_normal_param_estimate(), util_normal_stats_tbl()

Author

Steven P. Sanderson II, MPH

Examples

tidy_normal()
#> # A tibble: 50 × 7
#>    sim_number     x       y    dx       dy     p       q
#>    <fct>      <int>   <dbl> <dbl>    <dbl> <dbl>   <dbl>
#>  1 1              1  0.920  -3.64 0.000224 0.821  0.920 
#>  2 1              2  0.166  -3.50 0.000595 0.566  0.166 
#>  3 1              3  0.0983 -3.37 0.00140  0.539  0.0983
#>  4 1              4 -0.231  -3.23 0.00293  0.409 -0.231 
#>  5 1              5 -1.17   -3.09 0.00544  0.121 -1.17  
#>  6 1              6  0.468  -2.95 0.00899  0.680  0.468 
#>  7 1              7 -1.16   -2.81 0.0133   0.124 -1.16  
#>  8 1              8  0.657  -2.68 0.0176   0.745  0.657 
#>  9 1              9 -0.729  -2.54 0.0213   0.233 -0.729 
#> 10 1             10  1.27   -2.40 0.0244   0.897  1.27  
#> # ℹ 40 more rows