I am trying to calibrate an option pricing model (nonlinear) with 3 parameters to estimate, but not sure how to do it in Julia. function GKprice(S0, K, r, T, σ, d, Flag = "call") normcdf(x) = cdf(Normal(0, 1), x) d1=(log(S0/K)+(r-d+σ*σ*0.5)*T)/(σ*sqrt(T)) d2=d1-σ*sqrt(T) …

Nonlinear least squares estimate

ChrisRackauckas February 22, 2018, 2:42am 6

Yes. And just throw a function over it so that you send f(p) to send it to the package.

Topic		Replies	Views
Fitting parameters of the model against data New to Julia curve-fitting	3	1712	July 22, 2022
Estimating parameters of a function for curve fitting Optimization (Mathematical) curve-fitting	11	5472	April 9, 2020
LsqFit.jl error on ODE data fitting Optimization (Mathematical) question , diffeq , fit	2	1626	March 8, 2019
Multivariate Nonlinear Regression Optimization (Mathematical)	9	4131	July 2, 2019
How can I tell Julia what are the parameters in a linear model? Statistics regression , fit , curve-fitting , glm , linear-regression	14	1659	September 26, 2022