Uniform: Uniform Distribution Class

Description

Mathematical and statistical functions for the Uniform distribution, which is commonly used to model continuous events occurring with equal probability, as an uninformed prior in Bayesian modelling, and for inverse transform sampling.

Value

Returns an R6 object inheriting from class SDistribution.

Constructor

Uniform$new(lower = 0, upper = 1, decorators = NULL, verbose = FALSE)

Constructor Arguments

Argument	Type	Details
`lower`	integer	lower distribution limit.
`upper`	integer	upper distribution limit.

decorators Decorator decorators to add functionality. See details.

Constructor Details

The Uniform distribution is parameterised with lower and upper as numerics.

Public Variables

Variable	Return
`name`	Name of distribution.
`short_name`	Id of distribution.
`description`	Brief description of distribution.

Public Methods

Accessor Methods	Link
`decorators()`	`decorators`
`traits()`	`traits`
`valueSupport()`	`valueSupport`
`variateForm()`	`variateForm`
`type()`	`type`
`properties()`	`properties`
`support()`	`support`
`symmetry()`	`symmetry`
`sup()`	`sup`
`inf()`	`inf`
`dmax()`	`dmax`
`dmin()`	`dmin`
`skewnessType()`	`skewnessType`
`kurtosisType()`	`kurtosisType`



Statistical Methods	Link
`pdf(x1, ..., log = FALSE, simplify = TRUE)`	`pdf`
`cdf(x1, ..., lower.tail = TRUE, log.p = FALSE, simplify = TRUE)`	`cdf`
`quantile(p, ..., lower.tail = TRUE, log.p = FALSE, simplify = TRUE)`	`quantile.Distribution`
`rand(n, simplify = TRUE)`	`rand`
`mean()`	`mean.Distribution`
`variance()`	`variance`
`stdev()`	`stdev`
`prec()`	`prec`
`cor()`	`cor`
`skewness()`	`skewness`
`kurtosis(excess = TRUE)`	`kurtosis`
`entropy(base = 2)`	`entropy`
`mgf(t)`	`mgf`
`cf(t)`	`cf`
`pgf(z)`	`pgf`
`median()`	`median.Distribution`
`iqr()`	`iqr`



Parameter Methods	Link
`parameters(id)`	`parameters`
`getParameterValue(id, error = "warn")`	`getParameterValue`
`setParameterValue(..., lst = NULL, error = "warn")`	`setParameterValue`



Validation Methods	Link
`liesInSupport(x, all = TRUE, bound = FALSE)`	`liesInSupport`
`liesInType(x, all = TRUE, bound = FALSE)`	`liesInType`



Representation Methods	Link
`strprint()`	`strprint`
`print()`	`print`
`summary(full = T)`	`summary.Distribution`
`plot()`	Coming Soon.
`qqplot()`	Coming Soon.

Details

The Uniform distribution parameterised with lower, $a$ , and upper, $b$ , limits is defined by the pdf, $f (x) = 1 / (b - a)$ for $- \infty < a < b < \infty$ .

The distribution is supported on $[a, b]$ .

References

McLaughlin, M. P. (2001). A compendium of common probability distributions (pp. 2014-01). Michael P. McLaughlin.

Examples

Run this code

# NOT RUN {
x <- Uniform$new(lower = -10, upper = 5)

# Update parameters
x$setParameterValue(lower = 2, upper = 7)
x$parameters()

# d/p/q/r
x$pdf(5)
x$cdf(5)
x$quantile(0.42)
x$rand(4)

# Statistics
x$mean()
x$variance()

summary(x)

# }

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