Journal ArticleDOI
On some simple, autoregression-based estimation and identification techniques for ARMA models
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In this article, simple estimators for general ARMA models and a corresponding identification method are presented, based on a matrix formed from the coefficients of an autoregressive approximation to the process of interest.Abstract:
SUMMARY We examine simple estimators for general ARMA models and a corresponding identification method. Both estimation and identification are based on a matrix formed from the coefficients of an autoregressive approximation to the process of interest. We show that a zero determinant of this matrix is necessary and sufficient for the existence of a common factor in autoregressive and moving average lag polynomials, and therefore for redundant parameters in the model. Simulation results suggest a close match between the empirical finite-sample distribution of the test statistic for model order reduction and its asymptotic distribution.read more
Citations
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Eight (and a half) deadly sins of spatial analysis
TL;DR: In this paper, the authors discuss some of the assumptions that are often made in the analysis of spatially structured data that can lead to misunderstandings about the nature of spatial data, the methods used to analyse them, and how results can be interpreted.
Journal ArticleDOI
Content horizons for univariate time-series forecasts
TL;DR: In this paper, the authors consider the problem of determining the horizon beyond which forecasts from univariate time series models of stationary processes add nothing to the forecast implicit in the unconditional mean.
Journal ArticleDOI
Endogenous thresholds and tests for asymmetry in US prime rate movements
TL;DR: In this paper, the authors test the hypothesis that movements in the prime rate are dependent upon the interest rate regime and find that the responsiveness of prime to changes in the Federal Funds rate is relatively symmetric, but that the speed of adjustment of prime is faster when there is a substantial deviation from the equilibrium relationship linking these rates.
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Practical Methods for Modeling Weak VARMA Processes: Identification, Estimation and Specification With a Macroeconomic Application
TL;DR: In this paper, the problem of developing practical methods for modeling weak VARMA processes was considered and the diagonal MA equation form and the final MA equilibria were proposed. But the problem was not addressed in this paper.
Posted Content
Multimodality in the GARCH Regression Model
Jurgen A. Doornik,Marius Ooms +1 more
TL;DR: In this paper, a refinement to the Nelson and Cao (1992) condi tions for a GARCH(2,q) model is presented, and it is shown how these can then be implemented by parameter transformations.
References
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Book
Time series analysis, forecasting and control
TL;DR: In this article, a complete revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970 is presented, focusing on practical techniques throughout, rather than a rigorous mathematical treatment of the subject.
Journal ArticleDOI
Time Series Analysis Forecasting and Control
TL;DR: This revision of a classic, seminal, and authoritative book explores the building of stochastic models for time series and their use in important areas of application forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control.
Journal ArticleDOI
Time Series Analysis: Forecasting and Control
TL;DR: Time Series Analysis and Forecasting: principles and practice as mentioned in this paper The Oxford Handbook of Quantitative Methods, Vol. 3, No. 2: Statistical AnalysisTime-Series ForecastingPractical Time-Series AnalysisApplied Bayesian Forecasting and Time Series AnalysisSAS for Forecasting Time SeriesApplied Time Series analysisTime Series analysisElements of Nonlinear Time Series analyses and forecastingTime series analysis and forecasting by Example.
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Introduction to Statistical Time Series
TL;DR: In this paper, Fourier analysis is used to estimate the mean and autocorrelations of the Fourier spectral properties of a Fourier wavelet and the estimated spectrum of the wavelet.