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Tidy Randomly Generated Gaussian Distribution Tibble

Source: R/random-tidy-normal.R
tidy_normal.Rd

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()

See also

Other Continuous Distribution: tidy_beta(), tidy_burr(), tidy_cauchy(), tidy_chisquare(), tidy_exponential(), tidy_f(), tidy_gamma(), tidy_generalized_beta(), tidy_generalized_pareto(), 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  0.170 -2.77 0.000542 0.567   0.170
#>  2 1              2 -1.56  -2.65 0.00131  0.0593 -1.56 
#>  3 1              3  0.931 -2.53 0.00294  0.824   0.931
#>  4 1              4 -0.793 -2.41 0.00607  0.214  -0.793
#>  5 1              5 -1.07  -2.29 0.0116   0.141  -1.07 
#>  6 1              6  0.750 -2.18 0.0208   0.773   0.750
#>  7 1              7  0.941 -2.06 0.0345   0.827   0.941
#>  8 1              8 -0.315 -1.94 0.0534   0.376  -0.315
#>  9 1              9 -0.555 -1.82 0.0777   0.290  -0.555
#> 10 1             10 -0.129 -1.70 0.106    0.449  -0.129
#> # ℹ 40 more rows