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Exponential smoothing and resampling techniques in time series prediction

Maria Manuela Neves, Clara Cordeiro (2010)

Discussiones Mathematicae Probability and Statistics

Time series analysis deals with records that are collected over time. The objectives of time series analysis depend on the applications, but one of the main goals is to predict future values of the series. These values depend, usually in a stochastic manner, on the observations available at present. Such dependence has to be considered when predicting the future from its past, taking into account trend, seasonality and other features of the data. Some of the most successful forecasting methods are...

Extremal behaviour of stationary processes: the calibration technique in the extremal index estimation

D. Prata Gomes, Maria Manuela Neves (2010)

Discussiones Mathematicae Probability and Statistics

Classical extreme value methods were derived when the underlying process is assumed to be a sequence of independent random variables. However when observations are taken along the time and/or the space the independence is an unrealistic assumption. A parameter that arises in this situation, characterizing the degree of local dependence in the extremes of a stationary series, is the extremal index, θ. In several areas such as hydrology, telecommunications, finance and environment, for example, the...

Extremal (in)dependence of a maximum autoregressive process

Marta Ferreira (2013)

Discussiones Mathematicae Probability and Statistics

Maximum autoregressive processes like MARMA (Davis and Resnick, [5] 1989) or power MARMA (Ferreira and Canto e Castro, [12] 2008) have singular joint distributions, an unrealistic feature in most applications. To overcome this pitfall, absolute continuous versions were presented in Alpuim and Athayde [2] (1990) and Ferreira and Canto e Castro [14] (2010b), respectively. We consider an extended version of absolute continuous maximum autoregressive processes that accommodates both asymptotic tail...

Extreme order statistics in an equally correlated Gaussian array

Mateusz Wiśniewski (1994)

Applicationes Mathematicae

This paper contains the results concerning the weak convergence of d-dimensional extreme order statistics in a Gaussian, equally correlated array. Three types of limit distributions are found and sufficient conditions for the existence of these distributions are given.

Extreme values and kernel estimates of point processes boundaries

Stéphane Girard, Pierre Jacob (2004)

ESAIM: Probability and Statistics

We present a method for estimating the edge of a two-dimensional bounded set, given a finite random set of points drawn from the interior. The estimator is based both on a Parzen-Rosenblatt kernel and extreme values of point processes. We give conditions for various kinds of convergence and asymptotic normality. We propose a method of reducing the negative bias and edge effects, illustrated by some simulations.

Extreme values and kernel estimates of point processes boundaries

Stéphane Girard, Pierre Jacob (2010)

ESAIM: Probability and Statistics

We present a method for estimating the edge of a two-dimensional bounded set, given a finite random set of points drawn from the interior. The estimator is based both on a Parzen-Rosenblatt kernel and extreme values of point processes. We give conditions for various kinds of convergence and asymptotic normality. We propose a method of reducing the negative bias and edge effects, illustrated by some simulations.

Extremes of spheroid shape factor based on two dimensional profiles

Daniel Hlubinka (2006)

Kybernetika

The extremal shape factor of spheroidal particles is studied. Three dimensional particles are considered to be observed via their two dimensional profiles and the problem is to predict the extremal shape factor in a given size class. We proof the stability of the domain of attraction of the spheroid’s and its profile shape factor under a tail equivalence condition. We show namely that the Farlie–Gumbel–Morgenstern bivariate distributions gives the tail uniformity. We provide a way how to find normalising...

Funcionales de mínima g-divergencia y sus estimadores asociados (II).

Francisco Javier Cano Sevilla, M.ª Pilar Lasala Calleja (1984)

Trabajos de Estadística e Investigación Operativa

Se realizan dos estudios de simulación para comprobar el comportamiento asintóticamente robusto del estimador de mínima g-divergencia para dos elecciones notables de la función g.

Funcionales de mínima g-divergencia y sus estimadores asociados (I).

Francisco José Cano Sevilla, M.ª Pilar Lasala Calleja (1984)

Trabajos de Estadística e Investigación Operativa

Se introducen los funcionales de mínima g-divergencia y sus estimadores asociados. Se prueba la existencia y robustez del funcional y la convergencia del estimador asociado.

Fuzzy empirical distribution function: Properties and application

Gholamreza Hesamian, S. M. Taheri (2013)

Kybernetika

The concepts of cumulative distribution function and empirical distribution function are investigated for fuzzy random variables. Some limit theorems related to such functions are established. As an application of the obtained results, a method of handling fuzziness upon the usual method of Kolmogorov-Smirnov one-sample test is proposed. We transact the α -level set of imprecise observations in order to extend the usual method of Kolmogorov-Smirnov one-sample test. To do this, the concepts of fuzzy...

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