Hi,all I am doing a nonlinear regression and I am going to use nls. To Minimize:sum{(Y-BS(s,x,r,t,v)) ^2} a<-nls(Y~BS(s,x,r,t,v)) BS is the black-scholes model. BS<-function(s,x,r,t,v){ d1=(ln(s/x)+v^2*t/2)/(v*t^(0.5)) d2=(ln(s/x)-v^2*t/2)/(v*t^(0.5)) c=e^(rt)*(s*N(d1)-x*N(d2)) } where s,x,r,t are known numbers But v is dertermined by a linear regression: ln(v)=a0+a1*n+a2*n^2 a0,a1 and a2 are the ones to be estimated. How can write the code for these nonlinear regression? thanks Ted -- View this message in context: http://www.nabble.com/How-to-solve-this-nonlinear-regression-problem--tp20541306p20541306.html Sent from the R help mailing list archive at Nabble.com.