demand = table2array (mainData(9:62 , 2:21));
That is a 2D array.
expDemand = expValue(demand, meanDemandResize, stdDemandResize);
The array is passed as the first parameter to expValue()
function [expValue] = expValue(x , mu , sigma)
Where it is received under the name x
for i=1:x
where the 2D array is used as the upper bound for a for loop.
In MATLAB, when you use a non-scalar as a bound in a colon operation, MATLAB uses the first element of the array. The for loop is not iterating over the elements of x in any way: it is equivalent to
for i = 1 : x(1,1)
Then
y1 = cdf('Normal',x-1,mu,sigma); %% Cumulative Normal Dist. for Integer Value x-1
y2 = cdf('Normal',x,mu,sigma); %% Cumulative Normal Dist. for Integer Value x
y3 = y2- y1; %% Difference between Cum. N. Dist. (x- (x-1))
y4 = y3 .* x; %% Expected Value Difference Between * Value
Those steps involving processing all of x but are independent of the loop control variable, and those steps overwrite all of the variables involved completely. So each iteration of the for loop, those lines calculate exactly the same thing.
y5 = y5 + y4; %% Calculation of Expected Value
Except there. y5 was initialized to 0 before the for i loop. If you think about what is happening, with y4 being the same each iteration, the end result is going to be the same as if you had not done any for loop and had instead done
if x(1,1) >= 1
y1 = cdf('Normal',x-1,mu,sigma); %% Cumulative Normal Dist. for Integer Value x-1
y2 = cdf('Normal',x,mu,sigma); %% Cumulative Normal Dist. for Integer Value x
y3 = y2- y1; %% Difference between Cum. N. Dist. (x- (x-1))
y4 = y3 .* x; %% Expected Value Difference Between * Value
%repeated addition is the same as multiplication
y5 = y4 .* floor(x(1,1));
else
y5 = 0;
end
