analyzesleep.jl

function testsleep()
    sleeptimes = logspace(-3,1,50)
    actual_sleeptimes = map(sleeptimes) do st
        @elapsed sleep(st)
    end
    sleeptimes, actual_sleeptimes
end
sleeptimes, actual_sleeptimes = testsleep()
diff = actual_sleeptimes-sleeptimes
plot(sleeptimes, [diff diff./sleeptimes], xlabel="Sleeptimes", ylabel=["Absolute difference" "Relative difference"],
    xscale=:log10, yscale=[:linear :log10], ylims=[(0,1e-2) :auto], layout=2, legend=false)


A = log.(sleeptimes).^(0:4)'
x = A\log.(actual_sleeptimes)
e = log.(actual_sleeptimes) - A*x
predicted_time(t) = exp((log(t).^(0:4)')*x)
predicted_difference(t) = predicted_time(t)-t
plot(sleeptimes, [actual_sleeptimes predicted_time.(sleeptimes)], lab=["Actual", "Predicted"], xlabel="Sleeptime", yscale=:log10, xscale=:log10)
plot(sleeptimes, [abs.(diff-predicted_difference.(sleeptimes)) abs.(diff-predicted_difference.(sleeptimes))./sleeptimes],
        xlabel="Sleeptimes", ylabel=["Absolute prediction error" "Relative prediction error"],
        xscale=:log10, yscale=[:identity :log10], ylims=[(0,1e-2) :auto],
        layout=2, legend=false)

# Estimated parameters stat. significant?
σ² = var(e)
Σ = σ²*inv(A'A)
p05 = abs.(x)./sqrt.(diag(Σ)) .> 1.96