Bayesian forecasting and dynamic models (2nd ed.)
Bayesian forecasting and dynamic models (2nd ed.)
Improved frequency selective filters
Computational Statistics & Data Analysis - Special issue: Computational econometrics
New Introduction to Multiple Time Series Analysis
New Introduction to Multiple Time Series Analysis
New algorithms for dating the business cycle
Computational Statistics & Data Analysis
Forecasting daily time series using periodic unobserved components time series models
Computational Statistics & Data Analysis
Introduction to the special issue on statistical signal extraction and filtering
Computational Statistics & Data Analysis
An iterated parametric approach to nonstationary signal extraction
Computational Statistics & Data Analysis
Decomposition of time series models in state-space form
Computational Statistics & Data Analysis
Econometric methods of signal extraction
Computational Statistics & Data Analysis
Evaluation of likelihood functions for Gaussian signals
IEEE Transactions on Information Theory
Editorial: 2nd Special Issue on Statistical Signal Extraction and Filtering
Computational Statistics & Data Analysis
General linear mixed model and signal extraction problem with constraint
Journal of Multivariate Analysis
Removing seasonality under a changing regime: Filtering new car sales
Computational Statistics & Data Analysis
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Signal extraction deals with weighting the available observations in order to estimate a latent feature of interest. A signal extraction method is linear if the feature is measured by a possibly time-varying linear combination of the available observations. Linear methods play an important role since they are well understood, easy to apply, and are a key ingredient in more elaborate nonlinear and non-Gaussian models. The focus is on the main methods for inference about parametric and semiparametric unobserved components models formulated as linear mixed models and state space models and establish the connections between best linear unbiased prediction, penalised least squares and recursive methods of signal extraction. The methods are illustrated with reference to the traditional problem of extracting the cycle and the trend from economic time series.