visualize.continuous: Graphing function for Continuous Distributions.

In coatless/visualize: Graph Probability Distributions with User Supplied Parameters and Statistics

Graphing function for Continuous Distributions.

Description

Handles how continuous distributions are graphed. Users should not use this function. Instead, users should use visualize.it().

Usage

visualize.continuous(dist, stat = c(0, 1), params, section = "lower")

Arguments

dist	contains a supported continuos distribution shortname.
stat	a statistic to obtain the probability from. When using the "bounded" condition, you must supply the parameter as stat = c(lower_bound, upper_bound). Otherwise, a simple stat = desired_point will suffice.
params	A list that must contain the necessary parameters for each distribution. For example, params = list(mu = 1, sd = 1) would be for a normal distribution with mean 1 and standard deviation 1. If you are not aware of the parameters for the distribution, consider using the visualize.dist_name functions listed under the "See Also" section.
section	Select how you want the statistic(s) evaluated via ⁠section=⁠ either "lower","bounded", "upper", or"tails"

Author(s)

James Balamuta

See Also

visualize.it(), visualize.beta(), visualize.chisq(), visualize.exp(), visualize.gamma(), visualize.norm(), visualize.unif(), visualize.cauchy(), visualize.f(), visualize.lnorm(), visualize.t(), visualize.wilcox(), visualize.logis().

Examples

# Function does not have dist look up, must go through visualize.it
visualize.it(dist='norm', stat = c(0,1), params = list(mu = 1, sd = 1), section = "bounded")

coatless/visualize documentation built on Nov. 15, 2023, 4:12 a.m.