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Inputs

Index

Types

UncertaintyQuantification.Parameter Type
julia
Parameter(value::Real, name::Symbol)

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

Examples

julia
julia> Parameter(3.14, )
Parameter(3.14, )

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UncertaintyQuantification.RandomVariable Type
julia
RandomVariable(dist::UnivariateDistribution, name::Symbol)

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

Examples

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

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

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UncertaintyQuantification.EmpiricalDistribution Type
julia
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
julia
Interval(lb::Real, up::real, name::Symbol)

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

Examples

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

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UncertaintyQuantification.ProbabilityBox Type
julia
ProbabilityBox{T}(p::AbstractVector{Interval}, name::Symbol)

Defines an ProbabilityBox from a Vector of Interval, name UnivariateDistribution T. The number and order of parameters must match the parameters of the associated distribution from Distributions.jl.

Examples

julia
julia>  ProbabilityBox{Uniform}([Interval(1.75, 1.83, :a), Interval(1.77, 1.85, :b)], :l)
ProbabilityBox{Uniform}(Interval[Interval(1.75, 1.83, :a), Interval(1.77, 1.85, :b)], :l, 1.75, 1.85)
julia
julia>  ProbabilityBox{Normal}([Interval(0, 1, ), Interval(0.1, 1, )], :x)
ProbabilityBox{Normal}(Interval[Interval(0, 1, ), Interval(0.1, 1, )], :x, -Inf, Inf)

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Functions

UncertaintyQuantification.sample Function
julia
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
julia
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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