Displaying similar documents to “Exponential smoothing and resampling techniques in time series prediction”

Time series analysis: recursive methods and their modifications for time series with outliers and missing observations.

Tomás Cipra, Asunción Rubio, José Trujillo (1991)

Extracta Mathematicae

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The recursive methods are popular in time series analysis since they are computationally efficient and flexible enough to treat various changes in character of data. This paper gives a survey of the most important type of these methods including their classification and relationships existing among them. Special attention is devoted to i) robustification of some recursive methods, capable of facing outliers in time series, and ii) modifications of recursive methods for time series with...

Generalized probability functions.

Souto Martinez, Alexandre, Silva González, Rodrigo, Sangaletti Terçariol, César Augusto (2009)

Advances in Mathematical Physics

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Some problems of exponential smoothing

Tomáš Cipra (1989)

Aplikace matematiky

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The paper deals with some practical problems connected with the classical exponential smoothing in time series. The fundamental theorem of the exponential smoothing is extended to the case with missing observations and an interpolation procedure in the framework of the exponential smoothing is described. A simple method of the exponential smoothing for multivariate time series is suggested.

Computational intensive methods for prediction and imputation in time series analysis

Maria Manuela Neves, Clara Cordeiro (2011)

Discussiones Mathematicae Probability and Statistics

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One of the main goals in times series analysis is to forecast future values. Many forecasting methods have been developed and the most successful are based on the concept of exponential smoothing, based on the principle of obtaining forecasts as weighted combinations of past observations. Classical procedures to obtain forecast intervals assume a known distribution for the error process, what is not true in many situations. A bootstrap methodology can be used to compute distribution...

Robust estimation based on spacings in weighted exponential models

Paweł Błażej, Jarosław Bartoszewicz (2007)

Applicationes Mathematicae

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Using Zieliński's (1977, 1983) formalization of robustness Błażej (2007) obtained uniformly most bias-robust estimates (UMBREs) of the scale parameter for some statistical models (including the exponential model), in a class of linear functions of order statistics, when violations of the models are generated by weight functions. In this paper the UMBRE of the scale parameter, based on spacings, in two weighted exponential models is derived. Extensions of results of Bartoszewicz (1986,...