Okudo, M. and Komaki, F. (2020).
Bayes extended estimator for curved exponential families,

accepted for publication in *IEEE Transactions on Information Theory*.

Yano, K., Kaneko, R., and Komaki, F. (2020).
Minimax predictive density for sparse count data,

accepted for publication in *Bernoulli*.

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 and 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, 2902–29.

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.

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.

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.

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.

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).