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This function will generate n random points from a chisquare distribution with a user provided, .df, .ncp, 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_chisquare(.n = 50, .df = 1, .ncp = 1, .num_sims = 1)

Arguments

.n

The number of randomly generated points you want.

.df

Degrees of freedom (non-negative but can be non-integer)

.ncp

Non-centrality parameter, must be non-negative.

.num_sims

The number of randomly generated simulations you want.

Value

A tibble of randomly generated data.

Details

This function uses the underlying stats::rchisq(), and its underlying p, d, and q functions. For more information please see stats::rchisq()

Author

Steven P. Sanderson II, MPH

Examples

tidy_chisquare()
#> # A tibble: 50 × 7
#>    sim_number     x      y      dx      dy      p      q
#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
#>  1 1              1 0.836  -2.55   0.00103 0.438  0.836 
#>  2 1              2 0.0345 -2.27   0.00281 0.0899 0.0345
#>  3 1              3 0.265  -1.98   0.00687 0.249  0.265 
#>  4 1              4 7.17   -1.69   0.0151  0.953  7.17  
#>  5 1              5 1.86   -1.41   0.0300  0.633  1.86  
#>  6 1              6 0.516  -1.12   0.0538  0.346  0.516 
#>  7 1              7 0.362  -0.832  0.0870  0.291  0.362 
#>  8 1              8 0.797  -0.546  0.128   0.428  0.797 
#>  9 1              9 3.13   -0.259  0.171   0.776  3.13  
#> 10 1             10 1.80    0.0277 0.208   0.624  1.80  
#> # … with 40 more rows