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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 3.08   -2.66  0.00143 0.772  3.08  
#>  2 1              2 0.0420 -2.40  0.00346 0.0991 0.0420
#>  3 1              3 0.308  -2.13  0.00766 0.268  0.308 
#>  4 1              4 4.08   -1.87  0.0156  0.845  4.08  
#>  5 1              5 0.0554 -1.61  0.0292  0.114  0.0554
#>  6 1              6 2.69   -1.35  0.0504  0.734  2.69  
#>  7 1              7 0.322  -1.09  0.0798  0.274  0.322 
#>  8 1              8 4.37   -0.823 0.117   0.861  4.37  
#>  9 1              9 5.45   -0.560 0.157   0.908  5.45  
#> 10 1             10 0.171  -0.298 0.195   0.200  0.171 
#> # ℹ 40 more rows