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- W4386775802 abstract "This chapter focuses on non-linear curve fitting. Since real empirical data can be complicated, using a model can help reduce the complexity by summarizing it using one or more parameter estimates. The chapter looks at the issue of parameter optimization and the whole class of computational techniques designed to solve it. Since different algorithms have various strengths and weaknesses in features, particular subdisciplines prefer a specific algorithm. The chapter also considers the well-established optimization algorithm called the downhill simplex algorithm. It references the <italic>pracma</italic> package to elaborate on how to fit curves to data in <italic>R</italic> language." @default.
- W4386775802 created "2023-09-16" @default.
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- W4386775802 date "2022-03-21" @default.
- W4386775802 modified "2023-09-27" @default.
- W4386775802 title "Non-linear curve fitting" @default.
- W4386775802 doi "https://doi.org/10.1093/hesc/9780192896599.003.0009" @default.
- W4386775802 hasPublicationYear "2022" @default.
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