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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 -1.16  -3.52 0.000249 0.124   -1.16 
#>  2 1              2  0.657 -3.39 0.000711 0.745    0.657
#>  3 1              3 -0.729 -3.25 0.00177  0.233   -0.729
#>  4 1              4  1.27  -3.12 0.00385  0.897    1.27 
#>  5 1              5 -0.670 -2.99 0.00735  0.251   -0.670
#>  6 1              6  1.02  -2.85 0.0124   0.846    1.02 
#>  7 1              7  0.978 -2.72 0.0185   0.836    0.978
#>  8 1              8 -1.54  -2.59 0.0250   0.0622  -1.54 
#>  9 1              9 -2.44  -2.45 0.0312   0.00726 -2.44 
#> 10 1             10 -0.344 -2.32 0.0371   0.365   -0.344
#> # ℹ 40 more rows