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Persistent link: https://www.econbiz.de/10010955366
Persistent link: https://www.econbiz.de/10010955367
We consider a model for sensory profiling data including translation, rotation and scaling. We compare two methods to calculate an overall consensus from several data matrices: GPA and STATIS. These methods are briefly illustrated and explained under our model. A series of simulations to compare...
Persistent link: https://www.econbiz.de/10010955368
The aim of detecting outliers in a multivariate sample can be pursued in different ways. We investigate here the performance of several simultaneous multivariate outlier identification rules based on robust estimators of location and scale. It has been shown that the use of estimators with high...
Persistent link: https://www.econbiz.de/10010955369
Persistent link: https://www.econbiz.de/10010955370
Persistent link: https://www.econbiz.de/10010955371
A method for constructing approximative tests for arbitrary linear hypotheses on variance components in unbalanced mixed linear models is derived. The idea of cell mean models is used to derive independent and x2 - distributed mean squares. These modified mean squares are combined to generalized...
Persistent link: https://www.econbiz.de/10010955372
When comparing methods for classification, often the rating relies on their prediction accuracy alone. One reason for this is that this is the aspect that can be most easily measured. Yet, often one wants to learn more about the problem than only how to predict. The interpretation of the...
Persistent link: https://www.econbiz.de/10010955373
A simple method is given to calculate the multivariate process capability index Cp * as defined by Taam et al. (1993) and discussed by Kotz & Johnson (1993). It is shown that using this index is equivalent to using the smallest univariate Cp -value to determine the capability of a process.
Persistent link: https://www.econbiz.de/10010955374
In this paper we show that the recent notion of regression depth can be used as a data-analytic tool to measure the amount of separation between successes and failures in the binary response framework. Extending this algorithm allows us to compute the overlap in data sets which are commonly...
Persistent link: https://www.econbiz.de/10010955375