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Everything about Innovation method

Statistical estimation method

In statistics, the Innovation method provides an estimator for the parameters of stochastic differential equations given a time series of observations of the state variables. In the framework of continuous-discrete state space models, the innovation estimator is obtained by maximizing the log-likelihood of the corresponding discrete-time innovation process with respect to the parameters. The innovation estimator can be classified as a M-estimator, a quasi-maximum likelihood estimator or a prediction error estimator depending on the inferential considerations that want to be emphasized. The innovation method is a system identification technique for developing mathematical models of dynamical systems from measured data and for the optimal design of experiments. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Innovation methodA 5-minute orientation
  2. Skim a recent paper: Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times methodInfluential work since 2022
  3. Pick up a classic book: The Innovator's DilemmaThe most-reprinted book on the subject
  4. Read the landmark paper: Green process innovation, green product innovation, and corporate financial performance: A content analysis methodCited 1,231 times
  5. Go sideways: Bayes estimatorA closely related topic
  6. Go sideways: Toroidal coordinatesA closely related topic

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🗂️ The subject at a glance

  1. Background
  2. Discrete-time innovation process
  3. Innovation estimator
  4. Approximate Innovation estimators
  5. Software

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

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