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.
You can install the package in the usual way:
using Pkg
Pkg.add("Odrpack")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]