Smoothness Priors Analysis of Time Series von Kitagawa, Genshiro, Gersch, Will

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Smoothness Priors Analysis of Time Series von Kitagawa, Genshiro, Gersch, Will

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A smoothness priors time-varying AR coefficient modeling of nonstationary covariance time series von Kitagawa, G., Gersch, W.

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A Smoothness Priors-State Space Modeling of Time Series with Trend and Seasonality von Kitagawa, Genshiro, Gersch, Will

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A Smoothness Priors-State Space Modeling of Time Series with Trend and Seasonality von Kitagawa, Genshiro, Gersch, Will

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Smoothness priors modeling of seafloor bathymetric data von Gersch, Will

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The Prediction of Time Series With Trends and Seasonalities von Gersch, Will, Kitagawa, Genshiro

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Multivariate autoregressive time semes modeling: one scalar autoregressive model at-A-time von Gersch, Will, Stone, David

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A smoothness priors long AR model method for spectral estimation von Kitagawa, G., Gersch, W.

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Discrete Time Series Synthesis of Randomly Excited Structural System Response von Gersch, Will, Luo, Susan

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Automatic Classification of Electroencephalograms: Kullback-Leibler Nearest Neighbor Rules von Gersch, Will, Martinelli, F., Yonemoto, J., Low, M. D., McEwan, J. A.

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Multivariate autoregressive time series modeling : one scalar autoregressive model at-a-time von GERSCH, W, STONE, D

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Parametric time series models for multivariate EEG analysis von Gersch, Will, Yonemoto, James

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Smoothness priors transfer function estimation von Gersch, Will, Kitagawa, Genshiro

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Causality or driving in electrophysiological signal analysis von Gersch, Will

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Discrimination in stationary and non-stationary time series von Gersch, Will

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Discrimination in stationary and non-stationary time series von Gersch, Will

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The smoothing problem — a state space recursive computational approach: Applications to econometric time series with trends and seasonalities von Gersch, Will, Brotherton, Tom

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"A Smoothness Priors - State Space Modeling of Time Series With Trend and Seasonality" (TM) von KITAGAWA, GENSHIRO, Gersch, Will

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ARMA model eigenvalues and an amount of information measure features for automatic classification of multivariate EEG's von Gersch, Will

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