MATLAB - least square curve fit for multiple independent variables -

i have following function:

i'd coefficients least squares method matlab function lsqcurvefit.

the problem is, don't know, if it's possible use function when function t has multiple independent variables , not one. so, according link should have multiple xdata vectors - this:

lsqcurvefit(f, [1 1 1], nprocs, ndoms, ndof, measuredvals) 

do know how it?

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my attempt

i've tried define objective function this

f = @(c, x) c(1)*x(2).^(c(2)*x(1).^c(3)) + (c(4) + c(5)*x(1))/x(3); 

and use lsqcurvefit this

lsqcurvefit(f, [1 1 1], [ndoms ndof nprocs], measuredvals), 

but there's problem, measuredvals vector of size 56x1, "xdata" matrix of size 56x3, i'm getting error:

index exceeds matrix dimensions.  error in factorizatonkglobregr>@(c,x)c(1)*x(2).^(c(2)*x(1).^c(3))+(c(4)+c(5)*x(1))/x(3)  error in lsqcurvefit (line 202)             initvals.f = feval(funfcn_x_xdata{3},xcurrent,xdata,varargin{:});  caused by:     failure in initial objective function evaluation. lsqcurvefit cannot continue. 

but how supposed this, when $t: \mathbb{r}^3 \rightarrow \mathbb{r}$?

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second attempt

i've changed objective function to

f = @(c, x) c(1)*x(:,2).^(c(2)*x(:,1).^c(3)) + (c(4) + c(5)*x(:,1))/x(:,3);, 

but error remains.

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my data

measuredvals = [ 0.1647815 0.06300775 0.05769325 0.04803725 0.04290825 0.0405065 0.03807525 0.03487725 0.284112 0.13495675 0.12740075 0.11109725 0.105036 0.11022575 0.100587 0.09803775 0.48695475 0.30563525 0.30084925 0.283312 0.2745085 0.271998 0.27472625 0.27103925 0.89953925 0.68234025 0.6783635 0.65540225 0.64421475 0.64214725 0.63949875 0.623119 1.588605 1.37335275 1.36082075 1.35097375 1.34813125 1.34932025 1.3519095 1.34521625 2.820884 2.63251325 2.640659 2.6338805 2.636361 2.62748 2.6233345 2.63821 4.81472975 4.65116425 4.664892 4.64225625 4.6734825 4.63981675 4.635483 4.6280245];  n = 56;  ndoms = []; i=1:n     ndoms = [ndoms; 288]; end  tmp = [         375         1029         2187         3993         6591         10125         14739]; ndof = []; i=1:7     j=1:8         ndof = [             ndof             tmp(i)];     end end  nprocs = []; i=1:7     nprocs = [nprocs; [1 2 3 4 6 8 12 24]']; end 

when tested objective function simulated c , x input, returned nxn matrix size of data set. shouldn't case. should single value each data set expect nx1 matrix. try updating function this

f = @(c, x) c(1).*x(:,2).^(c(2).*x(:,1).^c(3)) + (c(4) + c(5)*x(:,1))./x(:,3)

i added period divisor.