visualize.it: Visualize's Processing Function

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

Visualize's Processing Function

Description

Acts as a director of traffic and first line of error handling regarding submitted visualization requests. This function should only be used by advanced users.

Usage

visualize.it(
  dist = "norm",
  stat = c(0, 1),
  params = list(mu = 0, sd = 1),
  section = "lower",
  strict = c(0, 1)
)

Arguments

dist	a string that should be contain a supported probability distributions name in R. Supported continuous distributions: "beta", "chisq", "exp", "gamma", "norm", and "unif". Supported discrete distributions: "binom", "geom", "hyper", "nbinom", and "pois".
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 functions listed under the "See Also" section.
section	Select how you want the statistic(s) evaluated via ⁠section=⁠ either "lower","bounded", "upper", or"tails".
strict	Determines whether the probability will be generated as a strict (<, >) or equal to (<=, >=) inequality. ⁠strict=⁠ requires either values = 0 or =FALSE for strict OR values =1 or =TRUE for equal to. For bounded condition use: strict=c(0,1) or strict=c(FALSE,TRUE).

Value

Returns a plot of the distribution according to the conditions supplied.

Author(s)

James Balamuta

References

http://cran.r-project.org/web/views/Distributions.html

See Also

visualize.beta(), visualize.chisq(), visualize.exp(), visualize.gamma(), visualize.norm(), visualize.unif(), visualize.binom(), visualize.geom(), visualize.hyper(), visualize.nbinom(), visualize.pois().

Examples

# Defaults to lower tail evaluation
visualize.it(dist = 'norm', stat = 1, list(mu = 3 , sd = 2), section = "lower")

# Set to evaluate the upper tail.
visualize.it(dist = 'norm', stat = 1, list(mu=3,sd=2),section="upper")

# Set to shade inbetween a bounded region.
visualize.it(dist = 'norm', stat = c(-1,1), list(mu=0,sd=1), section="bounded")

# Gamma distribution evaluated at upper tail.
visualize.it(dist = 'gamma', stat = 2, params = list(alpha=2,beta=1),section="upper")

# Binomial distribution evaluated at lower tail.
visualize.it('binom', stat = 2, params = list(n=4,p=.5))

visualize documentation built on Nov. 13, 2023, 5:07 p.m.