Tidy Randomly Generated Gaussian Distribution Tibble — tidy_normal • TidyDensity
Description: 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.

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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)

## 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.

## 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_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_pareto1()`, `tidy_pareto()`, `tidy_t()`, `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 -0.912  -3.60 0.000267 0.181  -0.912
    #>  2 1              2  0.432  -3.47 0.000706 0.667   0.432
    #>  3 1              3  0.0670 -3.33 0.00168  0.527   0.0670
    #>  4 1              4 -1.73   -3.20 0.00361  0.0421 -1.73
    #>  5 1              5  0.512  -3.07 0.00698  0.696   0.512
    #>  6 1              6 -0.645  -2.93 0.0122   0.259  -0.645
    #>  7 1              7  0.275  -2.80 0.0195   0.608   0.275
    #>  8 1              8  0.0211 -2.66 0.0283   0.508   0.0211
    #>  9 1              9  0.703  -2.53 0.0378   0.759   0.703
    #> 10 1             10 -0.581  -2.39 0.0472   0.281  -0.581
    #> # ℹ 40 more rows