Estimated Models (estimated + models)

Distribution by Scientific Domains


Selected Abstracts


Robust adaptive tracking control of uncertain discrete time systems

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 9 2005
Shengping Li
Abstract In this paper, the problem of robust adaptive tracking for uncertain discrete-time systems is considered from the slowly varying systems point of view. The class of uncertain discrete-time systems considered is subjected to both ,,, to ,,, bounded unstructured uncertainty and external additive bounded disturbances. A priori knowledge of the dynamic model of the reference signal to be tracked is not completely known. For such problem, an indirect adaptive tracking controller is obtained by frozen-time controllers that at each time optimally robustly stabilize the estimated models of the plant and minimize the worst-case steady-state absolute value of the tracking error of the estimated model over the model uncertainty. Based on ,,, to ,,, stability and performance of slowly varying system found in the literature, the proposed adaptive tracking scheme is shown to have good robust stability. Moreover, a computable upper bound on the size of the unstructured uncertainty permitted by the adaptive system and a computable tight upper bound on asymptotic robust steady-state tracking performance are provided. Copyright © 2005 John Wiley & Sons, Ltd. [source]


Towards a coherent statistical framework for dense deformable template estimation

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 1 2007
S. Allassonnière
Summary., The problem of estimating probabilistic deformable template models in the field of computer vision or of probabilistic atlases in the field of computational anatomy has not yet received a coherent statistical formulation and remains a challenge. We provide a careful definition and analysis of a well-defined statistical model based on dense deformable templates for grey level images of deformable objects. We propose a rigorous Bayesian framework for which we prove asymptotic consistency of the maximum a posteriori estimate and which leads to an effective iterative estimation algorithm of the geometric and photometric parameters in the small sample setting. The model is extended to mixtures of finite numbers of such components leading to a fine description of the photometric and geometric variations of an object class. We illustrate some of the ideas with images of handwritten digits and apply the estimated models to classification through maximum likelihood. [source]


Dynamics of petroleum markets in OECD countries in a monthly VAR,VEC model (1995,2007)

OPEC ENERGY REVIEW, Issue 1 2008
Mehdi Asali
This paper contains some results of a study in which the dynamics of petroleum markets in the Organization for Economic Cooperation and Development (OECD) is investigated through a vector auto regression (VAR),vector error correction model. The time series of the model comprises the monthly data for the variables demand for oil in the OECD, WTI in real term as a benchmark oil price, industrial production in OECD as a proxy for income and commercial stocks of crude oil and oil products in OECD for the time period of January 1995 to September 2007. The detailed results of this empirical research are presented in different sections of the paper; nevertheless, the general result that emerges from this study could be summarised as follows: (i) there is convincing evidence of the series being non-stationary and integrated of order one I(1) with clear signs of co-integration relations between the series; (ii) the VAR system of the empirical study appears stable and restores its dynamics as usual, following a shock to the rate of changes of different variables of the model, taking between five and eight periods (months in our case); (iii) we find the lag length of 2 as being optimal for the estimated VAR model; (iv) significant impact of changes in the commercial crude and products' inventory level on oil price and on demand for oil is highlighted in our empirical study and in different formulations of the VAR model, indicating the importance of the changes in the stocks' level on oil market dynamics; and (v) income elasticity of deman for oil appears to be prominent and statistically significant in most estimated models of the VAR system in the long run, while price elasticity of demand for oil is found to be negligible and insignificant in the short run. However, while aggregate oil consumption does not appear to be very sensitive to the changes of oil prices (which is believed to be because of the so-called ,rebound effect' of oil (energy) efficiency in the macro level) in the macro level, the declining trend of oil intensity (oil used for production of unit value of goods and services), particularly when there is an upward trend in oil price, clearly indicates the channels through which persistent changes in oil prices could affect the demand for oil in OECD countries. [source]


Estimation and hedging effectiveness of time-varying hedge ratio: Flexible bivariate garch approaches

THE JOURNAL OF FUTURES MARKETS, Issue 1 2010
Sung Yong Park
Bollerslev's (1990, Review of Economics and Statistics, 52, 5,59) constant conditional correlation and Engle's (2002, Journal of Business & Economic Statistics, 20, 339,350) dynamic conditional correlation (DCC) bivariate generalized autoregressive conditional heteroskedasticity (BGARCH) models are usually used to estimate time-varying hedge ratios. In this study, we extend the above model to more flexible ones to analyze the behavior of the optimal conditional hedge ratio based on two (BGARCH) models: (i) adopting more flexible bivariate density functions such as a bivariate skewed- t density function; (ii) considering asymmetric individual conditional variance equations; and (iii) incorporating asymmetry in the conditional correlation equation for the DCC-based model. Hedging performance in terms of variance reduction and also value at risk and expected shortfall of the hedged portfolio are also conducted. Using daily data of the spot and futures returns of corn and soybeans we find asymmetric and flexible density specifications help increase the goodness-of-fit of the estimated models, but do not guarantee higher hedging performance. We also find that there is an inverse relationship between the variance of hedge ratios and hedging effectiveness. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:71,99, 2010 [source]