API
Missing docstring for pbox( x :: Array{Interval{T}, 1}, bounded = [true, true]) where T <: Real
. Check Documenter's build log for details.
Missing docstring for pbox( x :: Array{T, 2}, bounded = [true, true]) where T <: Real
. Check Documenter's build log for details.
Distributions.cdf
— MethodDistributions.cdf
— Methodcdf(s :: pbox, x :: Interval)
Returns interval bounds on cdf value in interval x
ProbabilityBoundsAnalysis.mass
— Methodmass(s :: pbox, lo :: Real, hi :: Real)
Returns bounds on probability mass in interval [lo, hi]
ProbabilityBoundsAnalysis.mass
— Methodmass(s :: pbox, x:: Interval)
Returns bounds on probability mass in interval x
ProbabilityBoundsAnalysis.makepbox
— Methodmakepbox(x...)
Returns an array of pboxes from an array of inputs (eg an array of intervals or reals).
Examples
julia> s = makepbox(interval(0,1))
Pbox: ~ ( range=[0.0, 1.0], mean=[0.0, 1.0], var=[0.0, 0.25])
julia> array = [interval(0, 1), interval(0, 2), 3];
julia> s = makepbox.(array)
3-element Vector{pbox}:
Pbox: ~ ( range=[0.0, 1.0], mean=[0.0, 1.0], var=[0.0, 0.25])
Pbox: ~ ( range=[0.0, 2.0], mean=[0.0, 2.0], var=[0.0, 1.0])
Pbox: ~ ( range=3.0, mean=3.0, var=0.0)
Statistics.mean
— MethodStatistics.var
— MethodStatistics.std
— MethodMissing docstring for env(x...)
. Check Documenter's build log for details.
Missing docstring for imp(x...)
. Check Documenter's build log for details.
ProbabilityBoundsAnalysis.normal
— Methodnormal(mean :: Interval, std :: Interval)
Normal shaped pbox. Parameters can be Real or Intervals.
Constructors
normal
N
gaussian
Examples
julia> a = normal(interval(0, 1), interval(1,2))
Pbox: ~ normal ( range=[-6.1805, 7.1805], mean=[0.0, 1.0], var=[1.0, 4.0])
See also: uniform
, lognormal
, meanMinMax
, plot
Missing docstring for uniform(min :: Interval, max :: Interval)
. Check Documenter's build log for details.
ProbabilityBoundsAnalysis.beta
— Methodbeta(α :: Interval, β :: Interval)
Beta shaped pbox. Parameters can be Real or Intervals.
Examples
julia> a = beta(2,interval(3,4))
Pbox: ~ beta ( range=[0.0, 1.0], mean=[0.33333, 0.4], var=[0.031746, 0.04])
See also: KN
, meanMinMax
, plot
ProbabilityBoundsAnalysis.lognormal
— Methodlognormal(μ :: Interval, std :: Interval)
Lognormal shaped pbox. Parameters can be Real or Intervals.
See also: KN
, meanMinMax
ProbabilityBoundsAnalysis.KN
— MethodKN(k :: Interval, n :: Interval)
k out of N confidence box (c-box), a pbox shaped confidence structure. Quantifies inferential uncertainty in binomial counts, where k successes were observed out of n trails. One sided or two sided confidence intervals may be drawn
Constructors
KN
kn
See also: meanMinMax
, plot
ProbabilityBoundsAnalysis.cut
— Methodcut(x :: pbox, p :: Real)
returns a vertical cut of a pbox at cdf value p, for p ∈ [0, 1]
Constructors
cut(x :: pbox, p :: Real)
cut(x :: pbox, p :: Interval)
Index
Distributions.cdf
Distributions.cdf
ProbabilityBoundsAnalysis.KN
ProbabilityBoundsAnalysis.beta
ProbabilityBoundsAnalysis.cut
ProbabilityBoundsAnalysis.lognormal
ProbabilityBoundsAnalysis.makepbox
ProbabilityBoundsAnalysis.mass
ProbabilityBoundsAnalysis.mass
ProbabilityBoundsAnalysis.normal
Statistics.mean
Statistics.std
Statistics.var