| 1. |
- Beckman, Stig-Inge, et al.
(författare)
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Alarm characteristics for a flood warning system with deterministic components
- 1990
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Ingår i: Journal of Time Series Analysis. - : Wiley. - 0143-9782 .- 1467-9892. ; 11:1, s. 1-18
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Tidskriftsartikel (refereegranskat)abstract
- A method for evaluating a predictor-based alarm system is studied in this paper. The predictor is composed of a deterministic component reflecting external information and a statistically based component for the error between the measurements and the external predictor. The aim of the predictor study is twofold: it is a means of interpreting the connections between the alarm and the catastrophe, and it can be used to select suitable alarm levels. As an application, the performance of a water-level predictor as part of a flood warning system has been evaluated. The result of this analysis shows that an alarm system which operates when the predictor reaches a certain level will tend to give either too many alarms or alarms that are out of phase with the catastrophe.''
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| 2. |
- Holst, Ulla, et al.
(författare)
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Recursive estimation in switching autoregressions with Markov regime
- 1994
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Ingår i: Journal of Time Series Analysis. - : Wiley. - 0143-9782 .- 1467-9892. ; 15:5, s. 489-506
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Tidskriftsartikel (refereegranskat)abstract
- A hidden Markov regime is a Markov process that governs the time or space dependent distributions of an observed stochastic process. We propose a recursive algorithm for parameter estimation in a switching autoregressive process governed by a hidden Markov chain. A common approach to the recursive estimation problem is to base the estimation on suboptimal modifications of Kalman filtering techniques. The main idea in this paper is to use the maximum likelihood method and from this develop a recursive EM algorithm.
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| 3. |
- Svensson, Anders, et al.
(författare)
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Optimal prediction of catastrophes in autoregressive moving-average processes
- 1996
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Ingår i: Journal of Time Series Analysis. - : Wiley. - 0143-9782 .- 1467-9892. ; 17:5, s. 511-531
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Tidskriftsartikel (refereegranskat)abstract
- Abstract. This paper presents an optimal predictor of level crossings, catastrophes, for autoregressive moving-average processes, and investigates the performance of the predictor. The optimal catastrophe predictor is the predictor that gives a minimal number of false alarms for a fixed detection probability. As a tool for evaluating, comparing and constructing the predictors a method using operating characteristics, i.e. the probability of correct alarm and the probability of detecting a catastrophe for the predictor, is used. An explicit condition for the optimal catastrophe predictor based on linear prediction of future process values is given and compared with a naive catastrophe predictor, which alarms when the predicted process values exceed a given level, and with some different approximations of the optimal predictor. Simulations of the different algorithms are presented, and the performance is shown to agree with the theoretical results. All results indicate that the optimal catastrophe predictor is far better than the naive predictor. They also show that it is possible to construct an approximate catastrophe predictor requiring fewer computations without losing too much of the optimal predictor performance.
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| 4. |
- Westerlund, Joakim, et al.
(författare)
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New improved tests for cointegration with structural breaks
- 2007
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Ingår i: Journal of Time Series Analysis. - : Wiley. - 0143-9782 .- 1467-9892. ; 28:2, s. 188-224
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Tidskriftsartikel (refereegranskat)abstract
- This article proposes Lagrange multiplier-based tests for the null hypothesis of no cointegration. The tests are general enough to allow for heteroskedastic and serially correlated errors, deterministic trends, and a structural break of unknown timing in both the intercept and slope. The limiting distributions of the test statistics are derived, and are found to be invariant not only with respect to the trend and structural break, but also with respect to the regressors. A small Monte Carlo study is also conducted to investigate the small-sample properties of the tests. The results reveal that the tests have small size distortions and good power relative to other tests.
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| 5. |
- Villani, Mattias, 1973-
(författare)
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Fractional Bayesian lag length inference in multivariate autoregressive processes
- 2001
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Ingår i: Journal of Time Series Analysis. - : Wiley-Blackwell Publishing Inc.. - 0143-9782 .- 1467-9892. ; 22:1, s. 67-86
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Tidskriftsartikel (refereegranskat)abstract
- The posterior distribution of the number of lags in a multivariate autoregression is derived under an improper prior for the model parameters. The fractional Bayes approach is used to handle the indeterminacy in the model selection caused by the improper prior. An asymptotic equivalence between the fractional approach and the Schwarz Bayesian Criterion (SBC) is proved. Several priors and three loss functions are entertained in a simulation study which focuses on the choice of lag length. The fractional Bayes approach performs very well compared to the three most widely used information criteria, and it seems to be reasonably robust to changes in the prior distribution for the lag length, especially under the zero-one loss.
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| 6. |
- Meitz, Mika, et al.
(författare)
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Stability of nonlinear AR-GARCH models
- 2008
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Ingår i: Journal of Time Series Analysis. - : Wiley: 12 months. - 1467-9892 .- 0143-9782. ; 29:3, s. 453-475
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Tidskriftsartikel (refereegranskat)abstract
- This article studies the stability of nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a nonlinear autoregression of order p [AR(p)] with the conditional variance specified as a nonlinear first-order generalized autoregressive conditional heteroskedasticity [GARCH(1,1)] model. Conditions under which the model is stable in the sense that its Markov chain representation is geometrically ergodic are provided. This implies the existence of an initial distribution such that the process is strictly stationary and beta-mixing. Conditions under which the stationary distribution has finite moments are also given. The results cover several nonlinear specifications recently proposed for both the conditional mean and conditional variance, and only require mild moment conditions.
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| 7. |
- Wahlberg, Bo
(författare)
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Estimation of ARMA Models via High-Order Autoregressive Approximations
- 1989
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Ingår i: Journal of Time Series Analysis. - : John Wiley & Sons. - 0143-9782 .- 1467-9892. ; 10:3, s. 283-299
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Tidskriftsartikel (refereegranskat)abstract
- In this paper the problem of estimating autoregressive moving-average (ARMA) models is dealt with by first estimating a high-order autoregressive (AR) approximation and then using the AR estimate to form the ARMA estimate. We show how to obtain an efficient ARMA estimate by allowing the order of the AR estimate to tend to infinity as the number of observations tends to infinity. This approach is closely related to the work of Durbin. By transforming the approach into the frequency domain, we can view it as an L2-norm model approximation of the relative error of the spectral factors. It can also be seen as replacing the periodogram estimate in the Whittle approach by a high-order AR spectral density estimate. Since L2-norm approximation is a difficult task, we replace it by a modification of a recent model approximation technique called balanced model reduction. By an example, we show that this technique gives almost efficient ARMA estimates without the use of numerical optimization routines.
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| 8. |
- Wahlberg, Bo, 1959-
(författare)
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Estimation of Autoregressive Moving-Average Models Via High-order Autoregressive Approximations
- 1989
-
Ingår i: Journal of Time Series Analysis. - : Wiley. - 0143-9782 .- 1467-9892. ; 10, s. 283-299
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper the problem of estimating autoregressive moving-average (ARMA) models is dealt with by first estimating a high-order autoregressive (AR) approximation and then using the AR estimate to form the ARMA estimate. We show how to obtain an efficient ARMA estimate by allowing the order of the AR estimate to tend to infinity as the number of observations tends to infinity. This approach is closely related to the work of Durbin. By transforming the approach into the frequency domain, we can view it as an L2-norm model approximation of the relative error of the spectral factors. It can also be seen as replacing the periodogram estimate in the Whittle approach by a high-order AR spectral density estimate. Since L2-norm approximation is a difficult task, we replace it by a modification of a recent model approximation technique called balanced model reduction. By an example, we show that this technique gives almost efficient ARMA estimates without the use of numerical optimization routines.
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| 9. |
- Wahlberg, Patrik, 1966-, et al.
(författare)
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Locally stationary harmonizable complex improper stochastic processes
- 2011
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Ingår i: Journal of Time Series Analysis. - Oxford : Wiley-Blackwell. - 0143-9782 .- 1467-9892. ; 32:1, s. 33-46
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Tidskriftsartikel (refereegranskat)abstract
- This article concerns continuous-time second-order complex-valued improper stochastic processes that are harmonizable and locally stationary in Silverman's sense. We study necessary and sufficient conditions for the property of local stationarity in the time and frequency domains. A sufficient condition by Silverman is generalized and extended to the improper case. We obtain a result on the absolute continuity of the complementary spectral measure with respect to the spectral measure, which is related to a spectral characterization of improper wide-sense stationary processes.
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| 10. |
- Saikkonen, Pentti, et al.
(författare)
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Testing for a Unit Root in Noncausal Autoregressive Models
- 2015
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Ingår i: Journal of Time Series Analysis. - : Wiley: 12 months. - 1467-9892 .- 0143-9782.
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Tidskriftsartikel (refereegranskat)abstract
- This work develops maximum likelihood-based unit root tests in the noncausal autoregressive (NCAR) model with a non-Gaussian error term formulated by Lanne and Saikkonen (2011, Journal of Time Series Econometrics 3, Issue 3, Article 2). Finite-sample properties of the tests are examined via Monte Carlo simulations. The results show that the size properties of the tests are satisfactory and that clear power gains against stationary NCAR alternatives can be achieved in comparison with available alternative tests. In an empirical application to a Finnish interest rate series, evidence in favour of an NCAR model with leptokurtic errors is found.
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