[julia-users] Solving a Bellman equation with Julia through function iteration: what I do wrong?

[Pileas]

OK, I have the following model in which I try to solve the Bellman equation 
through function iteration. However somewhere I am wrong.

This is the code:

=========================================================================

sigma = 1.5;             # utility parameter
delta = 0.1;             # depreciation rate
beta = 0.95;             # discount factor
alpha = 0.30;            # capital elasticity of output
nbk = 1000;              # number of data points in t
crit = 1;                # convergence criterion
epsi = 1e-6;             # convergence parameter
ks = ((1-beta*(1-delta))/(alpha*beta))^(1/(alpha-1));
dev = 0.9;               # maximal deviation from ste
kmin = (1-dev)*ks;       # lower bound on the grid
kmax = (1+dev)*ks;       # upper bound on the grid
dk = (kmax-kmin)/(nbk-1);          # implied increment
kgrid = linspace(kmin,kmax,nbk)';  # builds the grid
v = zeros(nbk,1);                  # value function
dr = zeros(nbk,1);                 # decision rule (will contain indices)

while crit > epsi;
    for i = 1:nbk

        #compute indexes for which consumption is positive
        tmp = (kgrid(i)^alpha+(1-delta)*kgrid(i)-kmin);
        imax = min(floor(tmp/dk)+1,nbk);

        #consumption and utility
        c = kgrid(i)^alpha+(1-delta)*kgrid(i)-kgrid(1:imax);
        util = (c.^(1-sigma)-1)/(1-sigma);

        # find value function
        (tv(i),dr(i)) = max(util+beta*v(1:imax));
    end;

    crit = max(abs(tv-v));          # Compute convergence criterion
    v = tv;                         # Update the value function
end

# Final solution

kp = kgrid(dr);
c = kgrid.^alpha+(1-delta)*kgrid-kp;
util= (c.^(1-sigma)-1)/(1-sigma);
======================================================================

It gives me the following error: ERROR: invalid assignment location