Robust time series analysis: a survey
Norbert Stockinger, Rudolf Dutter (1987)
Kybernetika
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Norbert Stockinger, Rudolf Dutter (1987)
Kybernetika
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Tomáš Mrkvička (2007)
Commentationes Mathematicae Universitatis Carolinae
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The minimum variance unbiased estimator of the intensity of intersections is found for stationary Poisson process of segments with parameterized distribution of primary grain with known and unknown parameters. The minimum variance unbiased estimators are compared with commonly used estimators.
František Štulajter (1987)
Aplikace matematiky
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The method of least wquares is usually used in a linear regression model for estimating unknown parameters . The case when is an autoregressive process of the first order and the matrix corresponds to a linear trend is studied and the Bayes approach is used for estimating the parameters . Unbiased Bayes estimators are derived for the case of a small number of observations. These estimators are compared with the locally best unbiased ones and with the usual least squares estimators. ...
Zbyněk Pawlas (2011)
Kybernetika
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Summary characteristics play an important role in the analysis of spatial point processes. We discuss various approaches to estimating summary characteristics from replicated observations of a stationary point process. The estimators are compared with respect to their integrated squared error. Simulations for three basic types of point processes help to indicate the best way of pooling the subwindow estimators. The most appropriate way depends on the particular summary characteristic,...