- Initialization: Start with an initial design, which can be randomly selected or based on some heuristic.
- Exchange Process: Iteratively exchange rows between the current design and a candidate set to improve the design's optimality.
- Convergence: Continue exchanging until no further improvement can be made, or until a specified number of iterations is reached.
Which algorithm type does rowexch use?
조회 수: 4 (최근 30일)
이전 댓글 표시
Hi, I looked through the documentation, but couldn't find an answer:
Which type of algorithm does 'rowexch' use?
- The Federov algorithm
- The Modified Federov Algorithm
- The K-Exchange Algorithm
- Or yet another algorithm?
댓글 수: 0
답변 (1개)
Aditya
2025년 2월 3일
Hi Tobias,
The 'rowexch' function in MATLAB is used for generating D-optimal designs, which are a type of experimental design. The algorithm behind 'rowexch' is based on the Modified Federov Algorithm. This algorithm iteratively improves the design by exchanging rows in a candidate set to maximize the determinant of the information matrix, which is the criterion for D-optimality.
Here's a brief overview of how the Modified Federov Algorithm works:
The Modified Federov Algorithm is particularly suited for handling large candidate sets and is widely used for generating optimal experimental designs.
Refer the following documentation for more details.
댓글 수: 0
참고 항목
카테고리
Help Center 및 File Exchange에서 Industrial Statistics에 대해 자세히 알아보기
제품
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!