im using the code in the blog post
model(xdata,p) = p[1]*cos(p[2]*xdata)+p[2]*sin(p[1]*xdata)
xdata = [-2,-1.64,-1.33,-0.7,0,0.45,1.2,1.64,2.32,2.9]
ydata =
[0.699369,0.700462,0.695354,1.03905,1.97389,2.41143,1.91091,0.919576,-0.730975,-1.42001]
beta, r, J = curve_fit(model, xdata, ydata, [1.0, 0.2])
# beta = best fit parameters
# r = vector of residuals
# J = estimated Jacobian at solution
@printf("Best fit parameters are: %f and %f",beta[1],beta[2])
@printf("The sum of squares of residuals is %f",sum(r.^2.0))
and my julia is 0.3.7-pre
On Tuesday, March 3, 2015 at 11:11:26 PM UTC+1, René Donner wrote:
>
> Can you post the code you are trying to run? Which Julia version are you
> on?
>
> The example given on https://github.com/JuliaOpt/LsqFit.jl works fine
> here on 0.3.6.
>
>
>
> Am 03.03.2015 um 22:55 schrieb Andrei Berceanu <[email protected]
> <javascript:>>:
>
> > i now get
> > `start` has no method matching start(::LsqFitResult{Float64})
> >
> > On Tuesday, March 3, 2015 at 10:41:11 PM UTC+1, René Donner wrote:
> > Looks like curve_fit has been moved to
> https://github.com/JuliaOpt/LsqFit.jl
> >
> >
> > Am 03.03.2015 um 22:30 schrieb Andrei Berceanu <[email protected]>:
> >
> > > i found this post concerning nonlinear curve fitting in Julia,
> > > http://www.walkingrandomly.com/?p=5181
> > > but it appears the curve_fit method no longer exists
> > >
> > > does anyone have an updated version?
> >
>
>
