Selected article for: "fitting square and objective function"

Author: Chowell, Gerardo
Title: Fitting dynamic models to epidemic outbreaks with quantified uncertainty: A primer for parameter uncertainty, identifiability, and forecasts
  • Document date: 2017_8_12
  • ID: 3aa8wgr0_32
    Snippet: In the simplest manner, model parameters can be estimated via least-square fitting of the model solution to the observed data (Banks, Hu, & Thompson, 2014) . This is achieved by searching for the set of parameters b Q ¼ ð b q 1 ; b q 2 ; …; b q m Þ that minimizes the sum of squared differences between the observed data y ti ¼ y t1 ; y t1 ; …; y tn and the corresponding model solution denoted by f ðt i ; QÞ. That is, the objective functi.....
    Document: In the simplest manner, model parameters can be estimated via least-square fitting of the model solution to the observed data (Banks, Hu, & Thompson, 2014) . This is achieved by searching for the set of parameters b Q ¼ ð b q 1 ; b q 2 ; …; b q m Þ that minimizes the sum of squared differences between the observed data y ti ¼ y t1 ; y t1 ; …; y tn and the corresponding model solution denoted by f ðt i ; QÞ. That is, the objective function is given by

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