Paper



  Reviewed Article (in press):

  1. Mineaki Ohishi, Kensuke Okamura, Yoshimichi Itoh, Hirofumi Wakaki & Hirokazu Yanagihara. (2024).
    Coordinate descent algorithm for generalized group fused Lasso.
    Behaviormetrika.
    DOI: 10.1007/s41237-024-00233-6 [Open Access].
    Technical Report: Hiroshma Statistical Research Group Technical Report, TR-No. 21-02
    R package: GGFL.
  2. Mariko Yamamura, Mineaki Ohishi & Hirokazu Yanagihara. (2024).
    Poisson regression with categorical explanatory variables via Lasso using the median as a baseline.
    Smart Innovation, Systems and Technologies (KES-IDT-24).
  3. Mineaki Ohishi, Hirokazu Yanagihara, Hirofumi Wakaki & Masahiko Ono. (2023).
    Stable estimation of the slant parameter in skew normal regression via an MM algorithm and ridge shrinkage.
    International Journal of Knowledge Engineering and Soft Data Paradigms.
    DOI: 10.1504/IJKESDP.2023.10057725 (Forthcoming).
    Technical Report: Hiroshma Statistical Research Group Technical Report, TR-No. 22-05

  Reviewed Article (published):

  1. Mineaki Ohishi. (2024).
    Generalized fused Lasso for grouped data in generalized linear models.
    Statistics and Computing, 34 (4), 124.
    DOI: 10.1007/s11222-024-10433-5 [Open Access].
    Technical Report: Hiroshma Statistical Research Group Technical Report, TR-No. 24-02
    R package: GFLglm.
  2. Mariko Yamamura, Mineaki Ohishi & Hirokazu Yanagihara. (2023).
    Additive Poisson regression via forced categorical covariates and generalized fused Lasso.
    Proceedings of the 27th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (eds. Tsihrintzis, G. A., Toro, C., Rios, S. A., Howlett, R. J. & Jain, L. C.),
    Procedia Computer Science, 225, 1987--1996.
    DOI: 10.1016/j.procs.2023.10.189 [Open Access].
  3. Ryoya Oda, Mineaki Ohishi, Yuya Suzuki & Hirokazu Yanagihara. (2023).
    An 𝓁2,0-norm constrained matrix optimization via extended discrete first-order algorithms.
    Hiroshima Mathematical Journal, 53 (3), 251--267.
    DOI: 10.32917/h2021058 [Open Access].
    Technical Report: Hiroshima Statistical Research Group Technical Report, TR-No. 21-08
  4. Mariko Yamamura, Mineaki Ohishi & Hirokazu Yanagihara. (2023).
    Spatio-temporal analysis of rates derived from count data using generalized fused Lasso.
    Proceedings of the 15th KES-IDT 2023 Conference (eds. Czarnowski, I., Howlett, R. J. & Jain, L. C.),
    Smart Innovation, Systems and Technologies, 352, 225--234.
    DOI: 10.1007/978-981-99-2969-6_20.
  5. Mineaki Ohishi, Koki Kirishima, Kensuke Okamura, Yoshimichi Itoh & Hirokazu Yanagihara. (2023).
    Geographically weighted sparse group Lasso: local and global variable selections for GWR.
    Proceedings of the 15th KES-IDT 2023 Conference (eds. Czarnowski, I., Howlett, R. J. & Jain, L. C.),
    Smart Innovation, Systems and Technologies, 352, 183--192.
    DOI: 10.1007/978-981-99-2969-6_16.
  6. Hiroko Solvang & Mineaki Ohishi. (2023).
    trec: An R package for trend estimation and classification to support integrated assessment of the marine ecosystem and environmental factors.
    SoftwareX, 21, 101309.
    DOI: 10.1016/j.softx.2023.101309 [Open Access].
    arXiv: 2209.06619.
    R package: trec.
  7. Mineaki Ohishi, Mariko Yamamura & Hirokazu Yanagihara. (2022).
    Coordinate descent algorithm of generalized fused Lasso logistic regression for multivariate trend filtering.
    Japanese Journal of Statistics and Data Science, 5 (2), 535--551.
    DOI: 10.1007/s42081-022-00162-2.
    Technical Report: Hiroshima Statistical Research Group Technical Report, TR-No. 21-06.
    R package: GFLlogit.
  8. Mineaki Ohishi, Keisuke Fukui, Kensuke Okamura, Yoshimichi Itoh & Hirokazu Yanagihara. (2021).
    Coordinate optimization for generalized fused Lasso.
    Communications in Statistics - Theory and Methods, 50 (24), 5955--5973.
    DOI: 10.1080/03610926.2021.1931888 [Open Access].
    Technical Report: Hiroshima Statistical Research Group Technical Report, TR-No. 19-07.
  9. Mariko Yamamura, Mineaki Ohishi & Hirokazu Yanagihara. (2021).
    Spatio-temporal adaptive fused Lasso for proportion data.
    Proceedings of the 13th KES-IDT 2021 Conference (eds. Czarnowski, I., Howlett, R. J. & Jain, L. C.),
    Smart Innovation, Systems and Technologies, 238, 479--489.
    DOI: 10.1007/978-981-16-2765-1_40.
  10. Mineaki Ohishi, Kensuke Okamura, Yoshimichi Itoh & Hirokazu Yanagihara. (2021).
    Optimizations for categorizations of explanatory variables in linear regression via generalized fused Lasso.
    Proceedings of the 13th KES-IDT 2021 Conference (eds. Czarnowski, I., Howlett, R. J. & Jain, L. C.),
    Smart Innovation, Systems and Technologies, 238, 457--467.
    DOI: 10.1007/978-981-16-2765-1_38.
    Technical Report: Hiroshima Statistical Research Group Technical Report, TR-No. 21-01.
  11. Mineaki Ohishi. (2021).
    Ridge parameters optimization based on minimizing model selection criterion in multivariate generalized ridge regression.
    Hiroshima Mathematical Journal, 51 (2), 177--226.
    DOI: 10.32917/h2020104 [Open Access].
    Technical Report: Hiroshima Statistical Research Group Technical Report, TR-No. 20-07.
  12. Mineaki Ohishi, Hirokazu Yanagihara & Shuichi Kawano. (2020).
    Equivalence between adaptive-Lasso and generalized ridge estimators in linear regression with orthogonal explanatory variables after optimizing regularization parameters.
    Annals of the Institute of Statistical Mathematics, 72 (6), 1501--1516.
    DOI: 10.1007/s10463-019-00734-2.
    Technical Report: Hiroshima Statistical Research Group Technical Report, TR-No. 19-05.
  13. Keisuke Fukui, Mineaki Ohishi, Mariko Yamamura & Hirokazu Yanagihara. (2020).
    A fast optimization method for additive model via partial generalized ridge regression.
    Proceedings of the 12th KES International Conference on Intelligent Decision Technologies (eds. Czarnowski, I., Howlett, R. J. & Jain, L. C.),
    Smart Innovation, Systems and Technologies, 193, 279--290.
    DOI: 10.1007/978-981-15-5925-9_24.
    R package: GRRMSC.
  14. Mineaki Ohishi, Hirokazu Yanagihara & Hirofumi Wakaki. (2020).
    Optimization of generalized Cp criterion for selecting ridge parameters in generalized ridge regression.
    Proceedings of the 12th KES International Conference on Intelligent Decision Technologies (eds. Czarnowski, I., Howlett, R. J. & Jain, L. C.),
    Smart Innovation, Systems and Technologies, 193, 267--278.
    DOI: 10.1007/978-981-15-5925-9_23.
    R package: GRRMSC.
  15. Mineaki Ohishi, Hirokazu Yanagihara & Yasunori Fujikoshi. (2020).
    A fast algorithm for optimizing ridge parameters in a generalized ridge regression by minimizing a model selection criterion.
    Journal of Statistical Planning and Inference, 204, 187--205.
    DOI: 10.1016/j.jspi.2019.04.010.
    Technical Report: Hiroshima Statistical Research Group Technical Report, TR-No. 17-07.
    R package: GRRMSC.

  Preprint:

  1. Mariko Yamamura, Hirokazu Yanagihara, Mineaki Ohishi, Keisuke Fukui, Hiroko Solvang, Nils Øien & Tore Haug. (2023).
    Estimation of spatial effects by generalized fused Lasso for nonuniformly sampled spatial data: an analysis of the body condition of common minke whales (Balaenoptera acutorostrata acutorostrata) in the Northeast Atlantic.
    Hiroshima Statistical Research Group Technical Report, TR-No. 23-05, Hiroshima University. [ PDF ]
    R package: amgfl.

  Bulletin (Japanese):

  1. Mineaki Ohishi & Hirokazu Yanagihara. (2017).
    Minimization algorithm of model selection criterion for optimizing tuning parameter in Lasso estimator when explanatory variables are orthogonal.
    RIMS Kôkyûroku, Research Institute for Mathematical Sciences, Kyoto University, Kyoto, 2047, 124--140.
    HANDLE: 2433/237035.

  Thesis: