Re: [julia-users] Julia computing problem in a loop

[Mauro]

> The (global) constants are nvar = 6, number of variables (Int64) and plags 
> = 6, number of lags in the vector autoregression (Int64), which are defined 
> previously in the programs.

did you actually declare those const:

const nvar=6

?

If not, this will impact your loop.

> function bb_update(bbj, bbcovj)
>
>      for j = 1:obs
>          bbcovj += capZ[(j-1)*nvar+1:j*nvar,:]'*( 
> inv(Om_e[(j-1)*nvar+1:j*nvar,:]) )*capZ[(j-1)*nvar+1:j*nvar,:] ; 
>          bbj += capZ[(j-1)*nvar+1:j*nvar,:]'*( 
> inv(Om_e[(j-1)*nvar+1:j*nvar,:]) )*yyy[:,j] ;
>      end
>
>      return (bbj, bbcovj)
> end

Any object you do not pass in as argument needs to be const, thus maybe
pass them as arguments instead:

function bb_update(bbj, bbcovj, yyy, Om_e, capZ)
    for j = 1:size(yyy,2)
        jj = (j-1)*nvar+1:j*nvar
        bbcovj += capZ[jj,:]'*(inv(Om_e[jj,:]) )*capZ[jj,:]
        bbj += capZ[jj,:]'*(inv(Om_e[jj,:]) )*yyy[:,j] 
    end
    return (bbj, bbcovj)
end

Also, note, Julia is fastest with unrolled loops as at the moment Julia
makes a copy when doing slices (this will change sometime).  However, as
you're doing an matrix inverse, that trick is not applicable here.

Have you seen the performance section in the manual?