Generalized jackknife semi-parametric estimators of the tail index.
Gomes, M.Ivette, Martins, M.João, Neves, Manuela (2002)
Portugaliae Mathematica. Nova Série
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Gomes, M.Ivette, Martins, M.João, Neves, Manuela (2002)
Portugaliae Mathematica. Nova Série
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Ana María Pérez-Marín (2008)
SORT
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The Nelson-Aalen estimator is widely used in biostatistics as a non-parametric estimator of the cumulative hazard function based on a right censored sample. A number of alternative estimators can be mentioned, namely, the naive local constant estimator (Guillén, Nielsen and Pérez-Marín, 2007) which provides improved bias versus variance properties compared to the traditional Nelson-Aalen estimator. Nevertheless, an empirical comparison of these two estimators has never been carried out....
Rakshith Jagannath, Neelesh S. Upadhye (2018)
Kybernetika
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The least absolute shrinkage and selection operator (LASSO) is a popular technique for simultaneous estimation and model selection. There have been a lot of studies on the large sample asymptotic distributional properties of the LASSO estimator, but it is also well-known that the asymptotic results can give a wrong picture of the LASSO estimator's actual finite-sample behaviour. The finite sample distribution of the LASSO estimator has been previously studied for the special case of...
María Del Carmen Pardo (1997)
Kybernetika
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J. Jurečková (1983)
Acta Universitatis Carolinae. Mathematica et Physica
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Sergey Tarima, Dmitri Pavlov (2006)
ESAIM: Probability and Statistics
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In many practical situations sample sizes are not sufficiently large and estimators based on such samples may not be satisfactory in terms of their variances. At the same time it is not unusual that some auxiliary information about the parameters of interest is available. This paper considers a method of using auxiliary information for improving properties of the estimators based on a current sample only. In particular, it is assumed that the information is available as a number of estimates...