Akima is "free for non-commercial use" but this may be a commercial
application.
Your solution for 1 variable is called piecewise linear interpolation; there
are many ways to extend this to 2 variables. Piecewise linear on triangles,
for example, or piecewise bilinear. For the latter, given x=(x1,x2) and the
values at integers in f[,] compute the interpolated value as
i <- floor(x)
w <- x - i
m <- f[i[1]:(i[1]+1),i[2]:(i[2]+1)]
f1 <- c(1-w[1],w[1])%*%m
c(1-w[2],w[2])%*%f1
ie there are 4 nearest grid points and the weights are just products of the
1-variable weights.
Reid Huntsinger
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Liaw, Andy
Sent: Wednesday, September 29, 2004 11:09 AM
To: 'Naji'; r-help at stat.math.ethz.ch
Subject: RE: [R] Approximate a f(x,y)
The `akima' package on CRAN probably would help.
HTH,
Andy
> From: Naji
>
> Hi all,
>
>
> Running simulations, I'm generating market response to 2 factors
X&Y..
> There is no closed form for the market response.. The results
> are store in a
> matrix Z(X <- seq(.02,.98,.02), Y <- seq(.01,.19,.01))..
> For optmization purpose I need to approximate the values for
> any factor X in
> 0,02-0,98 and Y in 0,01-0,19
>
> How can I do it ?
>
> For one factor : Xn-1 < x <= Xn
> f(x)=(f(Xn-1)*(x-Xn-1)+f(Xn)*(Xn-x))/(Xn-Xn-1)
> I don't know how to generalize this for two factors..
>
>
> Thanks in Advance
> Naji
>
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