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Displaying 2541 –
2560 of
10055
In the wine AOC system, the regulation of quantities performed by the
professional
organizations is aimed to smooth the variations of the quality of the
wine due to the
variations in the climate that affect the quality of the grapes.
Nevertheless, this regulation
could be damaging to the consumers due to the price increase resulting
from the reduction of
the quantities sold on the market. We propose a stochastic control
model and a simulation tool
able to measure the effects of this mechanism...
Los procesos estocásticos estacionarios, autorregresivos y de medias móviles (ARMA), han sido estudiados en diversos ámbitos durante las dos últimas décadas (p.e. Brockwell-Davis, 1987), y se han utilizado con éxito en aplicaciones muy diversas.Uno de los aspectos al que parece que no se ha prestado demasiada atención es la descomposición aditiva de estos procesos, asociando cada componente a un polo de la función de transferencia del modelo ARMA. Esta descomposición aditiva, que llamaremos descomposición...
Edge-reinforced random walk (ERRW), introduced by Coppersmith and Diaconis in 1986 [8], is a random process which takes values in the vertex set of a graph and is more likely to cross edges it has visited before. We show that it can be represented in terms of a vertex-reinforced jump process (VRJP) with independent gamma conductances; the VRJP was conceived by Werner and first studied by Davis and Volkov [10, 11], and is a continuous-time process favouring sites with more local time. We calculate,...
Weak laws of large numbers (WLLN), strong laws of large numbers (SLLN), and central limit theorems (CLT) in statistical models differ from those in probability theory in that they should hold uniformly in the family of distributions specified by the model. If a limit law states that for every ε > 0 there exists N such that for all n > N the inequalities |ξₙ| < ε are satisfied and N = N(ε) is explicitly given then we call the law effective. It is trivial to obtain an effective statistical...
Important characteristics of any algorithm are its complexity and speed in real calculations. From this point of view, we analyze some algorithms for prediction in finite stationary time series. First, we review results developed by P. Bondon [1] and then, we derive the complexities of Levinson and a new algorithm. It is shown that the time needed for real calculations of predictions is proportional to the theoretical complexity of the algorithm. Some practical recommendations for the selection...
This paper is devoted to analysis of block multi-indexed higher-order covariance matrices, which can be used for the least-squares estimation problem. The formulation of linear and nonlinear least squares estimation problems is proposed, showing that their statements and solutions lead to generalized `normal equations', employing covariance matrices of the underlying processes. Then, we provide a class of efficient algorithms to estimate higher-order statistics (generalized multi-indexed covariance...
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