26. |
- Svensson, Anders
(författare)
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Event Prediction and Bootstrap in Time Series
- 1998
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Alarm systems are used in many situations, and should be as efficient as possible. In this thesis optimal predictive alarm systems, event predictors, are presented for general linear time series models with external signals. This family of process models include e.g. AR, ARMA, ARMAX and Box-Jenkins-type models. An optimal alarm system is characterized by having the least number of false alarms, for a specified probability of detecting the events, the catastrophes. The family of events treated is based on the time series and very general. When the process parameters are known and the noise distribution is Gaussian, the resulting optimal event predictor is based on predictions of future process values, and the alarm regions can be calculated in advance. Thus the event predictor can be used also in processes with a high sampling rate. It is also possible to construct an event predictor where a major part of the calculations can be made in real-time, which may be of advantage if the process parameters change. The peformance of the event predictors is examined using simulated as well as real data, and they are compared to simpler and more conventional alarm systems. When the noise distribution is unknown or the process parameters are unknown or time-varying, it is not possible to use the explicit event predictor above. However, statistical bootstrap techniques for calculating the distribution of the future process values can be applied to the problem. The presented bootstrap based event predictor demands large amounts of calculations for AR processes and even more so for ARX processes, but it is much more flexible than the event predictor discussed above, and the performance of the event predictors are comparable. Simulations are used to assess the performance. The bootstrap technique for ARX processes is also possible to apply to control problems, resulting in a new predictive control algorithm, the bootstrap control, which takes care of arbitrary loss functions and unknown noise distributions, even for small estimation sets. The bootstrap control algorithm has been tested through simulations and was found to work well for complicated loss functions and also for processes with slowly time-varying parameters.
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27. |
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28. |
- Malmgren, Helge, 1945
(författare)
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Learning by natural resonance.
- 1991
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Ingår i: Göteborg Psychological Reports. - 0301-0996. ; 21:6
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- I show with a theoretical argument and simulations that families of finite automata with randomly chosen transition tables, and whose output is alternatively steered by stimuli and a central randomly chosen controller, will automatically (!) show associative learning of stimuli, including learning of sequences.
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29. |
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31. |
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32. |
- Kaj, I, et al.
(författare)
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Probability of identity by descent in metapopulations
- 1999
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Ingår i: GENETICS. - 0016-6731. ; 152:3, s. 1217-1228
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Tidskriftsartikel (refereegranskat)abstract
- Equilibrium probabilities of identity by descent (IBD). for pairs of genes within individuals, for genes between individuals within subpopulations, and for genes between subpopulations are calculated in metapopulation models with fixed or varying colony s
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33. |
- Mattson, S
(författare)
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How to generate non-normal data for simulation of structural equation models
- 1997
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Ingår i: MULTIVARIATE BEHAVIORAL RESEARCH. - : LAWRENCE ERLBAUM ASSOC INC. ; 32:4
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- A procedure for generating non-normal data for simulation of structural equation models is proposed. A simple transformation of univariate random variables is used for the generation of data on latent and error variables under some restrictions for the e
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34. |
- Kadiyala, K. Rao, et al.
(författare)
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Forecasting with Generalized Bayesian Vector Autoregressions
- 1993
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Ingår i: Journal of Forecasting. - : John Wiley & Sons. - 0277-6693 .- 1099-131X. ; 12:3-4, s. 365-378
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Tidskriftsartikel (refereegranskat)abstract
- The effects of using different distributions to parameterize the prior beliefs in a Bayesian analysis of vector autoregressions are studied. The well-known Minnesota prior of Litterman as well as four less restrictive distributions are considered. Two of these prior distributions are new to vector autoregressive models. When the forecasting performance of the different parameterizations of the prior beliefs are compared it is found that the prior distributions that allow for dependencies between the equations of the VAR give rise to better forecasts.
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35. |
- Carling, K, et al.
(författare)
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An experimental comparison of gradient methods in econometric duration analysis
- 1998
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Ingår i: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - : ELSEVIER SCIENCE BV. - 0167-9473. ; 27:1, s. 83-97
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Tidskriftsartikel (refereegranskat)abstract
- Empirical duration analysis calls for numerical methods to search for a maximum of a non-linear likelihood function. The NEWTON method is probably a common choice. Yet, it might also be an unwise choice, as we demonstrate fitting a large empirical data s
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36. |
- Johansson, JE, et al.
(författare)
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Fifteen-year survival in prostate cancer - A prospective, population-based study in Sweden
- 1997
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Ingår i: JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION. - : AMER MEDICAL ASSOC. - 0098-7484. ; 277:6, s. 467-471
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Tidskriftsartikel (refereegranskat)abstract
- Objective.-To describe the natural history of initially untreated early-stage prostate cancer. A key secondary objective was to calculate long-term survival rates by stage, grade, and age at diagnosis. Design.-Prospective cohort study, Setting.-Population
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37. |
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38. |
- Achcar, JA, et al.
(författare)
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25 years of applied statistics
- 1998
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Ingår i: JOURNAL OF APPLIED STATISTICS. - : CARFAX PUBL CO. - 0266-4763. ; 25:1, s. 3-22
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Tidskriftsartikel (refereegranskat)
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50. |
- Andersson, Jonas, et al.
(författare)
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Random ranking of hospitals is unsound
- 1998
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Ingår i: CHANCE. - : Informa UK Limited. - 0933-2480 .- 1867-2280. ; 11:3, s. 34-39
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Tidskriftsartikel (refereegranskat)
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