Is there a method to select elements negatively proportionate to a categorical distribution? I have a categorical distribution which depicts the probability of bad choices. I want to select elements negatively proportionate to that categorical distribution, i.e., if my categorical distribution is [30%, 50%, 20%], then the second element (50%) will have the least probability to be selected, and I hope the last element (20%) will have the greatest probability to be selected. Is there such a method?

If your original probabilities are $p_i, i=1,\ldots d$, use as new probabilities $q_i$ with:
$$q_i = \frac{(1-p_i)}{\sum_{i=1}^d (1-p_i)}.$$
