Odrpack.jl

Description

This Julia package provides bindings for the well-known weighted orthogonal distance regression (ODR) solver odrpack95.

Orthogonal distance regression, also known as errors-in-variables regression, is designed primarily for instances when both the explanatory and response variables have significant errors.

Installation

You can install the package in the usual way:

using Pkg
Pkg.add("Odrpack")

Documentation and Usage

The following example demonstrates a simple use of the package. For more comprehensive examples and explanations, please refer to the documentation pages.

using Odrpack

function f!(x::Vector{Float64}, beta::Vector{Float64}, y::Vector{Float64})
    y .= beta[1] .* exp.(beta[2] .* x)
    return nothing
end

xdata = [0.982, 1.998, 4.978, 6.01]
ydata = [2.7, 7.4, 148.0, 403.0]

beta0 = [2.0, 0.5]
bounds = ([0.0, 0.0], [10.0, 0.9])

sol = odr_fit(
    f!,
    xdata,
    ydata,
    beta0,
    bounds=bounds,
    # rptfile="test_output.txt",
    # report=:long
)

println("Optimized β    :", sol.beta)
println("Optimized δ    :", sol.delta)
println("Optimized x + δ:", sol.xplusd)

Optimized β    :[1.633376, 0.9]
Optimized δ    :[-0.368861, -0.312730, 0.029286, 0.110314]
Optimized x + δ:[0.613138, 1.685269, 5.007286, 6.120314]