4 papers
Gaussian Process State-Space Modeling and Particle Filtering for Time Series Decomposition and Nonlinear Signal Extraction
Genshiro Kitagawa
Gaussian-process state-space models (GP-SSMs) provide a flexible nonparametric alternative for modeling time-series dynamics that are nonlinear or difficult to specify parametrical…
Emperical Study on Various Symmetric Distributions for Modeling Time Series
Genshiro Kitagawa
This study evaluated probability distributions for modeling time series with abrupt structural changes. The Pearson type VII distribution, with an adjustable shape parameter , p…
A Triginometric Seasonal Component Model and its Application to Time Series with Two Types of Seasonality
G. Kitagawa
A finite trigonometric series model for seasonal time series is considered in this paper. This component model is shown to be useful, in particular, for the modeling of time series…
Emperical Study on the Effect of Multi-Sampling in the Prediction Step of the Particle Filter
G. Kitagawa
Particle filters are applicable to a wide range of nonlinear, non-Gaussian state-space models and have already been applied to a variety of problems. However, there is a problem in…