Diagnosing seasonal shifts in time series using state space models

DOI10.1016/j.stamet.2005.09.012zbMath1248.93159OpenAlexW2083738867MaRDI QIDQ713705

Jeremy Penzer

Publication date: 19 October 2012

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2005.09.012

zbMATH Keywords

outliersstructural breaksKalman filter smootherseasonal breaksstate space form

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Estimation and detection in stochastic control theory (93E10)

Uses Software

• Ox
• SsfPack
• STAMP

Cites Work

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• Seasonal integration and cointegration
• The diffuse Kalman filter
• Smoothing and Interpolation with the State-Space Model
• Computing the likelihood and its dierivatives for a gaussian ARMA model
• A fast algorithm for signal extraction, influence and cross-validation in state space models
• Intervention Analysis with Applications to Economic and Environmental Problems
• Diagnosing Shocks in Time Series
• Exact Initial Kalman Filtering and Smoothing for Nonstationary Time Series Models
• Disturbance smoother for state space models
• The Effects of Seat Belt Legislation on British Road Casualties: A Case Study in Structural Time Series Modelling
• Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives
• Testing for Unit Roots in Seasonal Time Series

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