Statistical inference in mechanistic models: time warping for improved gradient matching

DOI10.1007/s00180-017-0753-zzbMath1417.65050DBLPjournals/cstat/NiuMRFH18OpenAlexW2742379511WikidataQ59603756 ScholiaQ59603756MaRDI QIDQ99665

Mu Niu, Maurizio Filippone, Benn Macdonald, Simon Rogers, Dirk Husmeier, Mu Niu, Dirk Husmeier, Maurizio Filippone, Simon Rogers, Benn Macdonald

Publication date: 9 August 2017

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-017-0753-z

zbMATH Keywords

dynamical systemsdifferential equationsobjective functionreproducing kernel Hilbert space

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Biomechanical solid mechanics (74L15)

Related Items (2)

R package for statistical inference in dynamical systems using kernel based gradient matching: KGode ⋮ KGode

Uses Software

• BioBayes
• deGradInfer
• PRMLT

Cites Work

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