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.
tidy_normal(.n = 50, .mean = 0, .sd = 1, .num_sims = 1, .return_tibble = TRUE)A tibble of randomly generated data.
The number of randomly generated points you want.
The mean of the randomly generated data.
The standard deviation of the randomly generated data.
The number of randomly generated simulations you want.
A logical value indicating whether to return the result as a tibble. Default is TRUE.
Steven P. Sanderson II, MPH
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()
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_pareto(),
tidy_pareto1(),
tidy_t(),
tidy_triangular(),
tidy_uniform(),
tidy_weibull(),
tidy_zero_truncated_geometric()
Other Gaussian:
tidy_inverse_normal(),
util_normal_param_estimate(),
util_normal_stats_tbl()