MATRIX FORMULAS FOR NONSTATIONARY ARIMA SIGNAL EXTRACTION

DOI10.1017/S0266466608080389zbMath1284.62585MaRDI QIDQ3632407

Tucker S. McElroy

Publication date: 11 June 2009

Published in: Econometric Theory (Search for Journal in Brave)

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (12)

Trends cycles and seasons: Econometric methods of signal extraction ⋮ Smoothing non-stationary time series using the discrete cosine transform ⋮ Forecasting continuous-time processes with applications to signal extraction ⋮ A Review of Some Modern Approaches to the Problem of Trend Extraction ⋮ Optimal signal extraction with correlated components ⋮ Signal Extraction for Non‐Stationary Multivariate Time Series with Illustrations for Trend Inflation ⋮ Statistical Properties of Model-Based Signal Extraction Diagnostic Tests ⋮ A nonparametric method for asymmetrically extending signal extraction filters ⋮ Maximum entropy extreme‐value seasonal adjustment ⋮ Trend estimation of financial time series ⋮ Identification of the differencing operator of a non-stationary time series via testing for zeroes in the spectral density ⋮ Casting vector time series: algorithms for forecasting, imputation, and signal extraction

Uses Software

• SsfPack

Cites Work

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• Seasonal Adjustment by Signal Extraction
• Signal extraction from nonstationary time series
• Computing observation weights for signal extraction and filtering
• An iterated parametric approach to nonstationary signal extraction
• Time series: theory and methods.
• Some efficient computational procedures for high order ARMA models
• Covariances for smoothed estimates in state space models
• An ARIMA-Model-Based Approach to Seasonal Adjustment
• INITIALIZING THE KALMAN FILTER FOR NONSTATIONARY TIME SERIES MODELS
• Decomposition of Seasonal Time Series: A Model for the Census X-11 Program
• Benchmarking by State Space Models
• Computation of asymmetric signal extraction filters and mean squared error for ARIMA component models
• Prediction of a noise-distorted, multivariate, non-stationary signal
• Measurement of a wandering signal amid noise

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