The "mapstd" function normalizes the input data row-wise (horizontally). Therefore, with your current implementation, you are actually normalizing each sample individually since you are putting your data one above the other in the following format (4 rows x 2 columns):
X =
[ sample1
sample2
sample3
sample4 ]
In order to use "mapstd" function to normalize each of your 2 predictor variables, you would need to store your data in the following format (2 row x 4 columns):
X = [ sample1 sample2 sample3 sample4]
Then, you can use "mapstd" function and get 2 means and 2 standard deviations (one for each predictor variable).
Making the necessary modification to the original data:
>> X = X'; % store sample column by column instead
>> [Xnew, PS] = mapstd(X);
>> XtestNew = mapstd('apply', Xtest, PS);
