optimize code with multiple for loops

My task is to fit experimental data with equation containing 7 unknow parameters. So I can check all posible parameter values my code contain 7 for loop, if parameter range is big calculations took a lot of time. Is there a way to get rid of for loops and speed up my calculations?

here is idea of my code. Each parameter range can be difrent

index = 1;

for par_1 = 1:0.1:10
    for par_2 = 1:0.1:10
        for par_3 = 1:1:10
            for par_4 = 1:1:5
                for par_5 = 1:1:100
                    for par_6 = 1:0.1:10
                        for par_7 = 1:0.1:100
                            
 % huge euation calculation
  
 % comparison with experiment data
 
 index = index+1
 
 % save parameter values for futher use
 table(index,1) = par_1;
 table(index,2) = par_2;
 table(index,3) = par_3;
 table(index,4) = par_3;
 table(index,5) = par_5;
 table(index,6) = par_6;
 table(index,7) = par_7;
                            
                        end
                    end
                end
            end
        end
    end
end

Answer 1

[Jan]

It depends on the magic parts "% huge euation calculation" and "% comparison with experiment data" if the loops can be avoided. Only posting the loops and just a rought comment for the actual calculations is not enought to suggest a solution.

Currently the only hint is to pre-allocate the output and not to use "table" as a name of a variable, because it is an important Matlab function.