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Persistent link: https://www.econbiz.de/10010982316
We consider a new estimator of scale for exponential samples which is most B-robust in the sense of Hampel et al. (1986). This estimator is compared with two other estimators which were proposed by Rousseeuw and Croux (1993) but for a Gaussian model. All three estimators have the same breakdown...
Persistent link: https://www.econbiz.de/10010955474
Observations which seem to deviate strongly from the main part of the data may occur in every statistical analysis. These observations usually labelled as outliers, may cause completely misleading results when using standard methods and may also contain information about special events or...
Persistent link: https://www.econbiz.de/10009295217
This paper deals with the problem of estimating the location parameter of a two parameter exponential distribution in case of contaminated data. Since in this case the sample minimum is an extremely unreliable estimator, robust alternatives are necessary. We investigate two types of estimators...
Persistent link: https://www.econbiz.de/10010982318
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The properties of Cpmk in the presence of asymmetric specification limits are discussed. It is shown that Cpmk tends to zero as the process variation increases and vice versa. Furthermore, if the process variation is small, Cpmk has its maximum near the target value but the maximum moves towards...
Persistent link: https://www.econbiz.de/10010955351
In this paper, we examine the German business cycle (from 1955 to 1994) in order to identify univariate and multivariate outliers as well as influence points corresponding to Linear Discriminant Analysis. The locations of the corresponding observations are compared and economically interpreted.
Persistent link: https://www.econbiz.de/10010955352
We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the Gaussian case all kernel M-estimators have the same limiting normal distribution. The motivation behind...
Persistent link: https://www.econbiz.de/10010955353