That works fine for me.  Possibly you have assigned one of the variables in the input?

While it shouldn't matter in this particular usage, note that gamma is a symbolic constant in Maple, akin to Pi.  Thus

evalf(gamma);
                       0.5772156649

@Markiyan Hirnyk Yes, I should have noted that charfcn is not terribly efficient.  More efficient than using remove/select, because it avoids creating a list, is

add(`if`(x<0,1,0), x = L);

@Markiyan Hirnyk Yes, I should have noted that charfcn is not terribly efficient.  More efficient than using remove/select, because it avoids creating a list, is

add(`if`(x<0,1,0), x = L);

Could you give a simple example with, say, a two-dimensional vector?

@Axel Vogt In this case the Maple code is a property of the figure(s). I was able to retrieve it by right-clicking on the figure(s) and selecting properties, then copying the Alternate Text field.

@ytyyutianyun By default, Maple use the greater-than sign (>) on the left-margin as a prompt.  When copying Maple code, these prompts must be removed.  The GUI's copy/paste commands generally do the right thing, the problem arises when you copy stuff to/from a different application.  Then you may have to delete the prompt characters.

One way to avoid this is to change the prompt.  I do this with

interface(prompt = "(**) "):

The result is that the prompt now corresponds to a delimited comment, so it will be ignored if copied into a Maple region.

@ytyyutianyun By default, Maple use the greater-than sign (>) on the left-margin as a prompt.  When copying Maple code, these prompts must be removed.  The GUI's copy/paste commands generally do the right thing, the problem arises when you copy stuff to/from a different application.  Then you may have to delete the prompt characters.

One way to avoid this is to change the prompt.  I do this with

interface(prompt = "(**) "):

The result is that the prompt now corresponds to a delimited comment, so it will be ignored if copied into a Maple region.

You left something out of your post, it only contains numerical assignments.

@pvrbik The help page could have a better example, one that demonstrates that, when successful, timelimit acts as a pass-through.  Tweaking the existing example (from ?timelimit):

f := proc(n) global i; for i to n do 2^i end do; return i; end proc:
n := timelimit(1, f(10^3));
                                   n := 1001
n := timelimit(1, f(10^6)); 
Error, (in f) time expired

Including the use of try wouldn't hurt:

try
   n := timelimit(1, f(10^6));
catch "time expired":
   n := i;
end try;
               n := 94313

I'll submit an SCR.

@pvrbik The help page could have a better example, one that demonstrates that, when successful, timelimit acts as a pass-through.  Tweaking the existing example (from ?timelimit):

f := proc(n) global i; for i to n do 2^i end do; return i; end proc:
n := timelimit(1, f(10^3));
                                   n := 1001
n := timelimit(1, f(10^6)); 
Error, (in f) time expired

Including the use of try wouldn't hurt:

try
   n := timelimit(1, f(10^6));
catch "time expired":
   n := i;
end try;
               n := 94313

I'll submit an SCR.

@yanin I won't be able to look at this for a couple days, but will respond then.

Yes, piecewise is more general (than `if`), but it is also more expensive.  Note that ?add has special evaluation rules so can deal with the `if` function.  For a discrete sum, I'd use add with `if`. 

Yes, piecewise is more general (than `if`), but it is also more expensive.  Note that ?add has special evaluation rules so can deal with the `if` function.  For a discrete sum, I'd use add with `if`. 

Consider profiling the code so that you can accurately determine where the bottlenecks lie.  The way to do this is to convert the code to a Maple procedure, use the ?CodeTools[Profiling] package to profile it, execute it, then print the profile results.

Starting with a worksheet I'd use File -> Export As to export the worksheet to a Maple script (*.mpl file), then edit the resulting file with a text editor to convert it to a procedure.  I took the liberty of doing so, Monte_Carlo_Slow_Do.mpl. Included in the file, after the assignment to the procedure Simulate, is the code to profile it, execute it, and print the results.  I haven't done so because I don't have the required spreadsheets, so there could be some issues with the code.

The first two bugs have been fixed in Maple 15.