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 ofn
for the current simulation.y
The randomly generated data point.dx
Thex
value from thestats::density()
function.dy
They
value from thestats::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.
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.
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()
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 -2.76 -3.86 0.000244 0.00287 -2.76
#> 2 1 2 0.528 -3.72 0.000751 0.701 0.528
#> 3 1 3 1.48 -3.57 0.00197 0.931 1.48
#> 4 1 4 0.788 -3.42 0.00439 0.785 0.788
#> 5 1 5 1.42 -3.27 0.00839 0.922 1.42
#> 6 1 6 -0.542 -3.13 0.0138 0.294 -0.542
#> 7 1 7 -1.72 -2.98 0.0198 0.0428 -1.72
#> 8 1 8 1.73 -2.83 0.0255 0.958 1.73
#> 9 1 9 -2.00 -2.68 0.0308 0.0228 -2.00
#> 10 1 10 0.181 -2.54 0.0372 0.572 0.181
#> # ℹ 40 more rows