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When prior information is available on the parameters of a non-linear model, it should influence the choice of the appropriate experimental design. We here investigate, for the multiresponse case, how prior information on the parameters in the form of a multivariate normal distribution can be used in selecting designs for parameter estimation. An example illustration how the precision of the prior knowledge can affect the positioning of the design points.
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Stored only when both papers are in the corpus — 64 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.