API
Modules
Types and constants
Functions and macros
BinnedModels.bin_centers
BinnedModels.bin_intervals
BinnedModels.bin_leftedges
BinnedModels.bin_rightedges
BinnedModels.bin_widths
BinnedModels.binned_likelihood
BinnedModels.binned_model
Documentation
BinnedModels.BinnedModels
— ModuleBinnedModels
A Julia package for statistical modeling of binned data, e.g. histograms.
BinnedModels.BinEdges
— TypeBinEdges{T<:Number} = AbstractVector{T}
Representation of a binning with n bins as n+1 edge points.
BinnedModels.BinnedModel
— Typestruct BinnedModels.BinnedModel
Respresents a statistical model for binned data.
User code should not instantiate BinnedModel
directly, but use binned_model
instead.
BinnedModels.Binning
— TypeBinning{T<:Number} = AbstractVector{<:AbstractInterval{T}}
Representation of a binning as a vector of intervals.
BinnedModels.bin_centers
— Functionbin_centers(binnig::Binning)
bin_centers(edges::BinEdges)
Returns the bin centers of a binning defined by a vector of edges.
BinnedModels.bin_intervals
— Functionfunction bin_intervals(edges::BinEdges, closed::Val = Val(:closedleft))::Binning
Returns a vector of n bin intervals, derived from a vector of n+1 bin edges.
BinnedModels.bin_leftedges
— Functionbin_leftedges(edges::BinEdges)
bin_leftedges(binnig::Binning)
Returns the left edges of a binning defined by a vector of edges.
BinnedModels.bin_rightedges
— Functionbin_rightedges(edges::BinEdges)
bin_rightedges(binnig::Binning)
Returns the right edges of a binning defined by a vector of edges.
BinnedModels.bin_widths
— Functionbin_widths(binnig::Binning)
bin_widths(binning::BinEdges)
Returns the bin widths of a binning defined by a vector of edges.
BinnedModels.binned_likelihood
— Functionbinned_likelihood(f_expectation, edges::Tuple{AbstractVector,...}, data::AbstractVector{<:Integer})
binned_likelihood(f_expectation, h::StatsBase.Histogram{<:Integer})
Constructs a binned likelihood object that is compatible with the DensityInterface API.
See also binned_model
.
BinnedModels.binned_model
— Functionbinned_model(f_expectation, edges::Tuple{AbstractVector,...})
Create a staticstical binned model from an density expectation function f_expectation
and a tuple of bin edges edges
.
See also binned_likelihood
.