Research

Paper

  1. Lund, A., S. W. Mogensen, and N. R. Hansen (2022). Soft Maximin Estimation for Heterogeneous Data. Scandinavian Journal of Statistics. arXiv.
  2. Lund, A. and N. R. Hansen (2019). Sparse Network Estimation for Dynamical Spatio-temporal Array Models. Journal of Multivariate Analysis. arXiv.
  3. Lund, A., M. Vincent, and N. R. Hansen (2017). Penalized estimation in large-scale generalized linear array models. Journal of Computational and Graphical Statistics. arXiv.
  4. Lund, A. (2017). Spatio-Temporal Modeling of Neuron Fields. Department of Mathematical Sciences, University of Copenhagen. Ph. D. thesis.
  5. Mogensen, S. W., A. Lund, and N. R. Hansen (2017). Sparse maximin aggregation of neuronal activity. SPARS2017.

Software

  1. Lund, A. (2022). pysmme: Soft Maximin Estimation for Large Scale Heterogeneous Data. Python package version 1.0. PyPi.
  2. Lund, A. (2022). FRESHD: Fast Robust Estimation of Signals in Heterogeneous Data. R package version 1.0. CRAN.
  3. Lund, A. (2021). SMME: Soft Maximin Estimation for Large Scale Heterogeneous Data. R package version 1.0. CRAN.
  4. Lund, A. (2018). dynamo: Fit a Stochastic Dynamical Array Model to Array Data. R package version 1.0. CRAN.
  5. Lund, A. (2017). SMMA: Soft Maximin Estimation for Large Scale Array-Tensor Models. R package version 1.0. CRAN.
  6. Lund, A. (2015). glamlasso: Penalization in Large Scale Generalized Linear Array Models. R package version 1.0. CRAN.