Fused Lasso Additive Model.

@article{Petersen2016FusedLA,
  title={Fused Lasso Additive Model.},
  author={Ashley Petersen and Daniela M. Witten and Noah Simon},
  journal={Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America},
  year={2016},
  volume={25 4},
  pages={1005-1025}
}
We consider the problem of predicting an outcome variable using p covariates that are measured on n independent observations, in a setting in which additive, flexible, and interpretable fits are desired. We propose the fused lasso additive model (FLAM), in which each additive function is estimated to be piecewise constant with a small number of adaptively-chosen knots. FLAM is the solution to a convex optimization problem, for which a simple algorithm with guaranteed convergence to a global… CONTINUE READING