Written it's O(n). Either way you'll probably be able to get the idea across, which is the most important part. You could also call it linear runtime.
big-omega and big-theta are similar mathematical concepts, but have different purposes. Big-omega describes the lower bound and big-theta describes both the upper and lower bounds.
In the case of the simple loop, omega(n) and theta(n) perfectly bound the runtime performance.
In gauging performance/runtime speed or memory usage we're concerned with the upper bound so big-O is ideal. Honestly I can't think of a single common example where either of these has been particularly interesting over big-O.
for a more thorough explanation.