Abstract
This chapter presents indirect methods of fitting parameters to ordinary differential equation models. Rather than solving the ODE, we instead obtain non-parametric estimates of the state trajectory and its derivative. This allows the right hand side of the ODE to be fit to the estimated derivatives, which is often numerically easier than the trajectory matching described in Chap. 7. We discuss the ways in which this approach allows us to diagnose model mis-specification, and develop confidence intervals for parameters. We also examine the related approach of fitting the trajectory to the integral of the right hand side function.
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Although Ramsay (1996) added some smoothing penalties to regularize \(\mathbf{B}(t)\) and this can be helpful
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Ramsay, J., Hooker, G. (2017). Two-Stage Least Squares or Gradient Matching. In: Dynamic Data Analysis. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7190-9_8
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DOI: https://doi.org/10.1007/978-1-4939-7190-9_8
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-7188-6
Online ISBN: 978-1-4939-7190-9
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