Citation
Kawaguchi E, Suchard MA, Liu Z, Li G (2020). “A surrogate L0 sparse Cox regression with applications to sparse high-dimensional massive sample size time-to-event data.” Statistics in Medicine, 39, 675-686. https://doi.org/10.1002/sim.8438.
@Article{,
author = {E. Kawaguchi and M. A. Suchard and Z. Liu and G. Li},
title = {A surrogate L0 sparse Cox regression with applications to sparse high-dimensional massive sample size time-to-event data},
journal = {Statistics in Medicine},
volume = {39},
pages = {675-686},
year = {2020},
url = {https://doi.org/10.1002/sim.8438},
}
Li N, Peng X, Kawaguchi E, Suchard MA, Li G (2021). “A scalable surrogate L0 sparse regression method for generalized linear models with applications to large scale data.” Journal of Statistical Planning and Inference, 213, 262-281. https://doi.org/10.1016/j.jspi.2020.12.001.
@Article{,
author = {N. Li and X. Peng and E. Kawaguchi and M. A. Suchard and G. Li},
title = {A scalable surrogate L0 sparse regression method for generalized linear models with applications to large scale data},
journal = {Journal of Statistical Planning and Inference},
volume = {213},
pages = {262-281},
year = {2021},
url = {https://doi.org/10.1016/j.jspi.2020.12.001},
}
Suchard MA, Simpson SE, Zorych I, Ryan P, Madigan D (2013). “Massive parallelization of serial inference algorithms for complex generalized linear models.” ACM Transactions on Modeling and Computer Simulation, 23, 10. https://dl.acm.org/doi/10.1145/2414416.2414791.
@Article{,
author = {M. A. Suchard and S. E. Simpson and I. Zorych and P. Ryan and D. Madigan},
title = {Massive parallelization of serial inference algorithms for complex generalized linear models},
journal = {ACM Transactions on Modeling and Computer Simulation},
volume = {23},
pages = {10},
year = {2013},
url = {https://dl.acm.org/doi/10.1145/2414416.2414791},
}