Selection finds the kth smallest element of a list of numbers. This algorithm is often used to find the median (\(k = \lfloor |S|/2 \rfloor\)). Information on this page is taken from Algorithms by Dasgupta et al.
Selection may be implemented with divide-and-conquer. For any number \(v\), imagine splitting list \(S\) into three categories: elements smaller than \(v\), those equal to \(v\), and those greater than \(v\). For example, if array
[2, 36, 5, 21, 8, 13, 11, 20, 5, 4, 1]
is split on \(v = 5\), the three subarrays (\(S_L\), \(S_v\), \(S_R\)) generated are
[2, 4, 1], [5, 5], [36, 21, 8, 13, 11, 20]
The search can instantly be narrowed down to one of these sublists. If we want, say, the eighth-smallest element of \(S\), we know it must be the third-smallest element of \(S_R\) since \(|S_L| + |S_v| = 5\). That is, selection(\(S\), 8) = selection(\(S_R\), 3). We then recurse on the appropriate sublist.
The three sublists can be computed in-place with linear time. With poor pivot choice the algorithm is \(O(n^2)\) (worse case). However, on average, the algorithm is \(O(n)\). Like quicksort, random pivot choice usually works well.