Readings in unobserved components models / edited by Andrew C. Harvey and Tommaso Proietti.

Includes bibliographical references and indexes.

PART ONE: SIGNAL EXTRACTION AND LIKELIHOOD INFERENCE FOR LINEAR UC MODELS -- Prediction theory for autoregressive-moving average processes / Peter Burridge, Kenneth F. Wallis -- Exact initial Kalman filtering and smoothing for nonstationary time series models / Siem Jan Koopman -- Smoothing and interpolation with the state-space model / Piet De Jong -- Diagnostic checking of unobserved-components time series models / Andrew C. Harvey, Siem Jan Koopman -- Nonparametric spline regression with autoregressive moving average errors / Robert Kohn ... [and others] -- PART TWO: UNOBSERVED COMPONENTS IN ECONOMIC TIME SERIES -- Univariate detrending methods with stochastic trends / Mark W. Watson -- Detrending, stylized facts and the business cycle / A.C. Harvey, A. Jaeger -- Stochastic linear trends: models and estimators / Augustín Maravall -- Estimation and seasonal adjustment of population means using data from repeated surveys / Danny Pfeffermann -- The modeling and seasonal adjustment of weekly observations / Andrew Harvey ... [and others] -- PART THREE: TESTING IN UNOBSERVED COMPONENTS MODELS -- Testing for deterministic linear trend in time series / Jukka Nyblom -- Are seasonal patterns constant over time? A test for seasonal stability / Fabio Canova, Bruce E. Hansen -- PART FOUR: NON-LINEAR AND NON-GAUSSIAN MODELS -- Time series models for count or qualitative observations / A.C. Harvey, C. Fernandes -- On Gibbs sampling for state space models / C.K. Carter, R. Kohn -- The simulation smoother for time series models / Piet De Jong, Neil Shephard -- Likelihood analysis of non-Gaussian measurement time series / Neil Shephard, Michael K. Pitt -- Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives / J. Durbin, S.J. Koopman -- On sequential Monte Carlo sampling methods for Bayesian filtering / Arnaud Doucet ... [and others]