Inputs

Index

• UncertaintyQuantification.EmpiricalDistribution
• UncertaintyQuantification.Interval
• UncertaintyQuantification.IntervalVariable
• UncertaintyQuantification.Parameter
• UncertaintyQuantification.ProbabilityBox
• UncertaintyQuantification.RandomVariable
• UncertaintyQuantification.sample
• UncertaintyQuantification.sample

Types

UncertaintyQuantification.Parameter Type

Parameter(value::Real, name::Symbol)

Defines a parameter value (scalar), with an input value and a name.

Examples

julia> Parameter(3.14, :π)
Parameter(3.14, :π)

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UncertaintyQuantification.RandomVariable Type

RandomVariable(dist::UnivariateDistribution, name::Symbol)

Defines a random variable, with a univariate distribution from Distributions.jl and a name.

Examples

julia> RandomVariable(Normal(), :x)
RandomVariable{Normal{Float64}}(Normal{Float64}(μ=0.0, σ=1.0), :x)

julia> RandomVariable(Exponential(1), :x)
RandomVariable{Exponential{Float64}}(Exponential{Float64}(θ=1.0), :x)

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UncertaintyQuantification.EmpiricalDistribution Type

EmpiricalDistribution(x::Vector{<:Real}, n::Integer=10000)

Creates an empirical distribution from the data given in `x` using kernel density estimation.
The kernel used is Gaussian and the bandwidth is obtained through the Sheather-Jones method.
The support is inferred from the kde using numerical root finding.
The `cdf` and `quantile` functions are linearly interpolated using `n` data points.

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UncertaintyQuantification.Interval Type

Interval(lb::Real, up::real)

Defines an Interval, with lower a bound, an upper bound.

This is a data type used internally and to construct p-boxes. For interval inputs see IntervalVariable.

Examples

jldoctest julia> Interval(0.10, 0.14) Interval(0.1, 0.14)

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UncertaintyQuantification.IntervalVariable Type

IntervalVariable(lb::Real, up::real, name::Symbol)

Defines an IntervalVariable input , with lower bound lb, upper bound ub and name.

This is an input type. To construct p-boxes with interval parameters use Interval

Examples

jldoctest julia> Interval(0.10, 0.14, :x) Interval(0.1, 0.14, :x)

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UncertaintyQuantification.ProbabilityBox Type

ProbabilityBox{T}(p::Dict{Symbol,Union{Real,Interval}})

Defines an ProbabilityBox from a Dict mapping each of the parameters of the UnivariateDistribution T to a Real or Interval.

Examples

julia>  ProbabilityBox{Uniform}(Dict(:a => Interval(1.75, 1.83), :b => Interval(1.77, 1.85)))
ProbabilityBox{Uniform}(Dict{Symbol, Union{Real, Interval}}(:a => [1.75, 1.83], :b => [1.77, 1.85]), 1.75, 1.85)

julia>  ProbabilityBox{Normal}(Dict(:μ => Interval(0, 1), :σ =>  Interval(0.1, 1)))
ProbabilityBox{Normal}(Dict{Symbol, Union{Real, Interval}}(:μ => [0, 1], :σ => [0.1, 1]), -Inf, Inf)

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Functions

UncertaintyQuantification.sample Function

sample(rv::RandomVariable, n::Integer=1)

Generates n samples from a random variable. Returns a DataFrame.

Examples

See also: RandomVariable

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UncertaintyQuantification.sample Function

sample(inputs::Vector{<:UQInput}, n::Integer=1)

Generates n correlated samples from a collection of inputs. Returns a DataFrame

See also: RandomVariable, Parameter

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