Parameter Estimation and Variable Selection for Big Systems of Linear Ordinary Differential Equations: A Matrix-Based Approach

DOI10.1080/01621459.2017.1423074zbMath1420.62102OpenAlexW2785275580MaRDI QIDQ5231494

Xing Qiu, Leqin Wu, Hulin Wu, Ya-Xiang Yuan

Publication date: 27 August 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357247

zbMATH Keywords

ordinary differential equationcomplex systemhigh dimensionseparable least squareseigenvalue updating algorithmmatrix-based variable selection

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Point estimation (62F10)

Related Items (3)

Dynamical modeling for non-Gaussian data with high-dimensional sparse ordinary differential equations ⋮ Identifiability analysis of linear ordinary differential equation systems with a single trajectory ⋮ Separable nonlinear least-squares parameter estimation for complex dynamic systems

Uses Software

• NEWUOA
• fda (R)

Cites Work

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