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Network constrained covariate coefficient and connection sign estimation

Author

Listed:
  • WEBER Matthias,

    (Bank of Lithuania and Vilnius University)

  • STRIAUKAS Jonas,

    (CORE, UCLouvain)

  • SCHUMACHER Martin,

    (University of Freiburg)

  • HARALD Binder,

    (University of Freiburg)

Abstract

Often, variables are linked to each other via a network. When such a network structure is known, this knowledge can be incorporated into regularized regression settings. In particular, an additional network penalty can be added on top of another penalty term, such as a Lasso penalty. However, when the type of interaction via the network is unknown (that is, whether connections are of an activating or a repressing type), the connection signs have to be estimated simultaneously with the covariate coefficients. This can be done with an algorithm iterating a connection sign estimation step and a covariate coefficient estimation step. We show detailed simulation results of such an algorithm. The algorithm performs well in a variety of settings. We also briefly describe the R-package that we developed for this purpose, which is publicly available.

Suggested Citation

  • WEBER Matthias, & STRIAUKAS Jonas, & SCHUMACHER Martin, & HARALD Binder,, 2018. "Network constrained covariate coefficient and connection sign estimation," LIDAM Discussion Papers CORE 2018018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2018018
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    Keywords

    network regression; network penalty; connection sign estimation; regularized regression;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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