Publications

Sei, T. and Komaki, F. (2022). A correlation-shrinkage prior for Bayesian prediction of the two-dimensional Wishart model,
   accepted for publication in Biometrika.

Matsuda, T., Homae, F., Watanabe, H., Taga G., and Komaki F. (2022). Oscillator decomposition of infant fNIRS data,
   accepted for publication in PLOS Computational Biology.

Yamanaka, Y., Kurata, S., Yano, K., Komaki, F., Shiina, T., and Kato, A. (2022). Structured regularization based local earthquake tomography for the adaptation to velocity discontinuities,
   Earth, Planets and Space. vol. 74. https://doi.org/10.1186/s40623-022-01600-x

Kurata, S., Kuroda, R., and Komaki, F. (2021). Statistical modeling for temporal dominance of sensations data incorporating individual characteristics of panelists: An application to data of milk chocolate,
   Journal of Food Science and Technology. https://doi.org/10.1007/s13197-021-05260-9

Komaki, F. (2021). Shrinkage priors for nonparametric Bayesian prediction of nonhomogeneous Poisson processes,
   IEEE Transactions on Information Theory, vol. 67, 5305 - 5317.

Oda, H. and Komaki, F. (2021). Shrinkage priors on complex-valued circular-symmetric autoregressive processes,
   IEEE Transactions on Information Theory, vol. 67, 5318 - 5333.

Okudo, M. and Komaki, F. (2021). Shrinkage priors for single-spiked covariance models,
   Statistics & Probability Letters, vol. 176, 109127

Yano, K., Shiina, T., Kurata, S., Kato, A., Komaki, F., Sakai, S., and Hirata, N. (2021).
   Graph-partitioning based convolutional neural network for earthquake detection using a seismic array.
   Journal of Geophysical Research: Solid Earth, vol. 126, e2020JB020269. https://doi.org/10.1029/2020JB020269

Okudo, M. and Komaki, F. (2021). Bayes extended estimators for curved exponential families,
   IEEE Transactions on Information Theory, vol. 67, 1088 - 1098.

Yano, K., Kaneko, R., and Komaki, F. (2021). Minimax predictive density for sparse count data,
   Bernoulli, vol. 27, 1212-1238.

Shibue, R. and Komaki, F. (2020). Deconvolution of calcium imaging data using marked point processes,
   PLOS Computational Biology; https://doi.org/10.1371/journal.pcbi.1007650.

Nakamura, K., Yano, K., and Komaki, F. (2020). Adjacency-based regularization for partially ranked data with non-ignorable missing,
   Computational Statistics & Data Analysis, vol. 145; doi:10.1016/j.csda.2019.106905.

Tanaka, T., Hirose, Y., and Komaki, F. (2020). Second-order matching prior family parametrized by sample size and matching probability,
   Statistical Papers, vol. 61, 1701-1717.

Matsuda, T., and Komaki, F. (2019). Empirical Bayes matrix completion,
   Computational Statistics & Data Analysis, vol. 137, 195–210.

Araki, K., Hirose, Y., and Komaki, F. (2019). Paired comparison models with age effects modeled as piecewise quadratic splines,
   International Journal of Forecasting, vol. 35, 733–740.

Takasu, Y, Yano, K, and Komaki, F. (2018). Scoring rules for statistical models on spheres,
   Statistics & Probability Letters, vol. 138, 111-115.

Komaki, F. and Biswas, A. (2018). Bayesian optimal response-adaptive design for binary responses using stopping rule,
   Statistical Methods in Medical Research, vol. 27, 891–904.

Koyama, T., Matsuda, T. and Komaki, F. (2017). Minimax estimation of quantum states based on the latent information priors,
   Entropy, vol. 19, 618; doi:10.3390/e19110618.

Shibue, R. and Komaki, F. (2017). Firing rate estimation using infinite mixture models and its application to neural decoding,
   Journal of Neurophysiology, vol. 118, 2902–2913.

Yano, K. and Komaki, F. (2017). Asymptotically minimax prediction in infinite sequence models,
   Electronic Journal of Statistics, vol. 11, 3165-3195.

Matsuda, T. and Komaki, F. (2017). Multivariate time series decomposition into oscillation components,
   Neural Computation, vol. 29, pp. 2055-2075.

Matsuda, T., Kitajo, K., Yamaguchi, Y., and Komaki, F. (2017). A point process modeling approach for investigating the effect of online brain activity on perceptual switching,
   NeuroImage, vol. 152, pp. 50-59.

Matsuda, T. and Komaki, F. (2017). Time series decomposition into oscillation components and phase estimation,
   Neural Computation, vol. 29, pp. 332-367.

Yano, K. and Komaki, F. (2017). Information criteria for prediction when the distributions of current and future observations differ,
   Statistica Sinica, vol. 27, pp. 1205-1223

Kojima, M. and Komaki, F. (2016). Relations between the conditional normalized maximum likelihood distributions and the latent information priors,
   IEEE Transactions on Information Theory, vol. 62, pp. 539-553.

Kojima, M. and Komaki, F. (2016). Determinantal point process priors for Bayesian variable selection in linear regression,
   Statistica Sinica, vol. 26, pp. 97-117.

Komaki, F. (2015). Simultaneous prediction for independent Poisson processes with different durations,
   Journal of Multivariate Analysis, vol. 141, pp. 35-48.

Matsuda, T. and Komaki, F. (2015). Singular value shrinkage priors for Bayesian prediction,
   Biometrika, vol. 102, pp. 843-854.

Hirose, Y. and Komaki, F. (2015). An estimation procedure for contingency table models based on the nested geometry,
   Journal of the Japan Statistical Society, vol. 45, pp. 57-75.

Komaki, F. (2015). Asymptotic properties of Bayesian predictive densities when the distributions of data and target variables are different,
   Bayesian Analysis, vol. 10, pp. 31-51.

Yano, K. and Komaki, F. (2014). Asymptotically constant-risk predictive densities when the distributions of data and target variables are different,
   Entropy, vol. 16, pp. 3026-3048.

Komaki, F. (2013). Bayesian testing of a point null hypothesis based on the latent information prior,
   Entropy, vol. 15, pp. 4416–4431.

Hirose, Y. and Komaki, F. (2013). Edge selection based on the geometry of dually flat spaces for Gaussian graphical models,
   Statistics and Computing, vol. 23, pp. 793–800.

Komaki, F. (2012). Asymptotically minimax Bayesian predictive densities for multinomial models,
   Electronic Journal of Statistics, vol. 6, pp. 934–957.

Komaki, F. (2011). Bayesian predictive densities based on latent information priors,
  Journal of Statistical Planning and Inference, vol. 141, pp. 3705–3715.

Nomura, S., Y. Ogata, F. Komaki, and S. Toda (2011). Bayesian forecasting of recurrent earthquakes and predictive performance for a small sample size,
  Journal of Geophysical Research, vol. 116, B04315, doi:10.1029/ 2010JB007917.

Tanaka, F. and Komaki, F. (2011). Asymptotic expansion of the risk difference of the Bayesian spectral density in the autoregressive moving average model,
  Sankhya Series A, vol. 73, pp. 162-184.

Hirose, Y. and Komaki, F. (2010). An extension of least angle regression based on the information geometry of dually flat spaces,
  Journal of Computational and Graphical Statistics, vol. 19, 1007-1023.

Inagaki, K. and Komaki, F. (2010). A modification of profile empirical likelihood for the exponential-tilt model,
  Statistics & Probability Letters, vol. 80, 997-1004.

Suzuki, T. and Komaki, F. (2010). On prior selection and covariate shift of beta-Bayesian prediction under alpha-divergence risk,
  Communications in Statistics - Theory and Methods, vol. 39, 1655-1673.

Komaki, F. (2009). Bayesian predictive densities based on superharmonic priors for the 2-dimensional Wishart model,
  Journal of Multivariate Analysis, vol. 100, 2137-2154.

Kobayashi, K., and Komaki, F. (2008). Bayesian shrinkage prediction for the regression problem,
  Journal of Multivariate Analysis, vol. 99, 1888-1905.

Tanaka, F. and Komaki, F. (2008). A superharmonic prior for the autoregressive process of the second order,
  Journal of Time Series Analysis, vol. 29, 444-452.

Nishimura, T. and Komaki, F. (2008). The information geometric structure of generalized empirical likelihood estimators,
  Communications in Statistics - Theory and Methods, vol. 37, 1867-1879.

Sei, T., and Komaki, F. (2008). Information geometry of small diffusions,
  Statistical Inference for Stochastic Processes, vol. 11, pp. 123-141.

Komaki, F. (2007). Bayesian prediction based on a class of shrinkage priors for location-scale models,
  Annals of the Institute of Statistical Mathematics, vol. 59, 135-146.

Sei, T., and Komaki, F. (2007). Bayesian prediction and model selection for locally asymptotically mixed normal models,
  Journal of Statistical Planning and Inference, vol. 137, 2523-2534.

Komaki, F. (2006). A class of proper priors for Bayesian simultaneous prediction of independent Poisson observables,
  Journal of Multivariate Analysis, vol. 97 1815-1828.

Komaki, F. (2006). Shrinkage priors for Bayesian prediction,
  The Annals of Statistics, vol. 34, 808-819.

Kobayashi, K., and Komaki, F. (2006). Information criteria for support vector machines,
  IEEE Transactions on Neural Networks, vol. 17, 571-577.

Tanaka, F. and Komaki, F. (2005). Bayesian predictive density operators for exchangeable quantum statistical models,
  Physical Review A, vol. 71, 052323.

Fushiki, T., Komaki, F., and Aihara, K. (2005). Nonparametric bootstrap prediction,
  Bernoulli, vol. 11, 293-307.

Fushiki, T., Komaki, F., and Aihara, K. (2004). On parametric bootstrapping and Bayesian prediction,
  Scandinavian Journal of Statistics, vol. 31, 403-416.

Komaki, F. (2004). Simultaneous prediction of independent Poisson observables,
  The Annals of Statistics, vol. 32, 1744-1769.

Komaki, F. (2004). Noninformative priors for prediction based on group models, in R. Fischer, R. Preuss, and U. von Toussaint (eds.),
  Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Garching, Germany 2004,
  AIP Conference Proceedings, American Institute of Physics, Melville, 525-532.

Tanaka, F., and Komaki, F. (2003). The sectional curvature of AR model manifolds,
  Tensor, vol. 64, 131-143.

Komaki, F. (2002). Bayesian predictive distribution with right invariant priors,
  Calcutta Statistical Association Bulletin, vol. 52, 171-179.

Komaki, F. (2001). A shrinkage predictive distribution for multivariate normal observables,
  Biometrika, vol. 88, 859-864.

Komaki, F.(2000). The theory of Predictive Distributions.
  The Transacion of the Institute of Electronics, Information and Communication Engineers A, Vol. J83-A, 612-619, (in Japanese).

Komaki, F. (1999). An estimating method for parametric spectral densities of Gaussian time series.
  Journal of Time Series Analysis, vol. 20, 31-50.

Komaki. F. (1996). On asymptotic properties of predictive distributions.
  Biometrika, vol. 83, 299-313.

Komaki, F. (1996). Homogeneous Gaussian Markov processes on general lattices.
  Advances in Applied Probability, vol. 28, 189-206.

Komaki, F. (1993). State-space modelling of time series sampled from continuous processes with pulses.
  Biometrika, vol. 80, 417-429.

Komaki, F. and Itoh, Y. (1992). A unified model for Kakutani's interval splitting and Renyi's random packing.
  Advances in Applied Probability, vol. 24, 502-505.

Ozaki, T., and Komaki, F. (1991). Statistical Identification of Nonlinear Systems with Application to Riverflow Prediction.
  Systems, Control and Information, Vol. 35, 331-341, (in Japanese).