In an amortized analysis, the time required to perform a sequence of data structure operations is average over all operation performed. Amortized analysis can be used to show that average cost of an operation is small, if one average over a sequence of operations, even though a single operation might be expensive. Unlike the average probability distribution function, the amortized analysis guarantees the 'average' performance of each operation in the worst case.

CLR covers the three most common techniques used in amortized analysis. The main difference is the way the cost is assign.

1. Aggregate Method
   • Computes an upper bound T(n) on the total cost of a sequence of n operations.
2. Accounting Method
   • Overcharge some operations early in the sequence. This 'overcharge' is used later in the sequence for pay operation that charges less than they actually cost.
3. Potential Method
   • Maintain the credit as the potential energy to pay for future operations.