lsqnonlin returns: Length of lower bounds is > length(x)

Hi

I recently just started using Matlab and am trying to find my way around. I am trying to use it to solve for unknown parameters for my X and Y dataset. I tried using the curvefit toolbox but it always result in a negative R^2 value. I am trying to use lsqnonlin function to find the optimized values for the unknown.

My FES.m file

function FES = unknown(x,Y)

K=x(1);
A=x(2);
v=x(3);
FES = ((Y/(1-Y)*exp(2*A*Y))^v)/K;

To evaluate 3 unknowns I used the FES.m file as follows

X =
1.0e-007 *

         0
    0.0001
    0.0003
    0.0005
    0.0007
    0.0014
    0.0035
    0.0069
    0.0692
    0.3460
    0.6920

Y =
       0
  0.2018
  0.2018
  0.2385
  0.1713
  0.1468
  0.3180
  0.3333
  0.1774
  0.6239
  0.9297

x0 =
  10000000           1           1

[x,resnorm] = lsqnonlin(@FES,x0,Y,X)

Which returns:

Warning: Length of lower bounds is > length(x); ignoring extra bounds. 
> In checkbounds at 27
  In lsqnsetup at 56
  In lsqnonlin at 191
Warning: Length of upper bounds is > length(x); ignoring extra bounds. 
> In checkbounds at 37
  In lsqnsetup at 56
  In lsqnonlin at 191

Exiting due to infeasibility: 2 lower bounds exceed the corresponding upper bounds.

I would appreciate if someone can point out what I am doing wrong, or if there is a better method to do this. Many thanks.

[Oleg Komarov]

What is the vector X? Do you want separate coefficients for X and Y?

You're using the syntax of lsqnonlin() incorrectly but I cannot help before you clarify the two points I raise.

[Sargondjani]

the syntax is: x = lsqnonlin(fun,x0,lb,ub)

so Y and X are lower and upper bounds... which contain more entries than x0 (scalar). this is why you get the error