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_numberThe current simulation number.xThe current value ofnfor the current simulation.yThe randomly generated data point.dxThexvalue from thestats::density()function.dyTheyvalue from thestats::density()function.pThe values from the resulting p_ function of the distribution family.qThe 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 -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
