Apologies for the confusion, but there isn't a commonly recognized method known as the "iteration method" specifically in the context of Design and Analysis of Algorithms (DAA). However, there are various techniques commonly used in algorithm analysis, such as the iterative algorithm design paradigm or iterative improvement techniques.

1. Iterative Algorithm Design: This approach involves designing algorithms that use iterative loops or iterations to solve a problem. In the analysis of such algorithms, you would typically consider factors such as the number of iterations, the operations performed within each iteration, and how these factors scale with the input size. The time complexity of the algorithm can be derived based on these considerations.

2. Iterative Improvement Techniques: Iterative improvement techniques are used for optimizing algorithms by iteratively refining an initial solution to achieve better results. Examples of iterative improvement techniques include the gradient descent algorithm for optimization problems and various search algorithms like iterative deepening depth-first search (IDDFS) or simulated annealing. The analysis of these techniques typically involves understanding the number of iterations required to converge to an optimal or near-optimal solution.

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