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Chapter and Conference Paper
Investigation of the Language in Germany and Austria Using Statistical Methods
On the basis of texts from the 18th century the German language is investigated. We emphasize not the use of words but the grammatical distribution of the words distinguished by codes. The relative frequencies...
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Chapter and Conference Paper
Outlier resistant estimators for canonical correlation analysis
Canonical correlation analysis studies associations between two sets of random variables. Its standard computation is based on sample covariance matrices, which are however very sensitive to outlying observati...
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Chapter and Conference Paper
A robust version of principal factor analysis
Our aim is to construct a factor analysis method that can resist the effect of outliers. We start with a highly robust initial covariance estimator, after which the factors can be obtained from maximum likelih...
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Article
Normal and lognormal data distribution in geochemistry: death of a myth. Consequences for the statistical treatment of geochemical and environmental data
All variables of several large data sets from regional geochemical and environmental surveys were tested for a normal or lognormal data distribution. As a general rule, almost all variables (up to more than 5...
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Article
Fitting multiplicative models by robust alternating regressions
In this paper a robust approach for fitting multiplicative models is presented. Focus is on the factor analysis model, where we will estimate factor loadings and scores by a robust alternating regression algor...
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Chapter and Conference Paper
Robust Redundancy Analysis by Alternating Regression
Given two groups of variables redundancy analysis searches for linear combinations of variables in one group that maximize the variance of the other group that is explained by each one of the linear combinatio...
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Article
Testing hypotheses with fuzzy data: The fuzzy p-value
Statistical hypothesis testing is very important for finding decisions in practical problems. Usually, the underlying data are assumed to be precise numbers, but it is much more realistic in general to conside...
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Article
Robust canonical correlations: A comparative study
Several approaches for robust canonical correlation analysis will be presented and discussed. A first method is based on the definition of canonical correlation analysis as looking for linear combinations of t...
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Article
Open AccessComparison of some linear regression methods – available in R – for a QSPR problem
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Article
Open AccessDiagnoses-related procedure bundles in outpatient care – results from a research project using secondary data
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Article
Ultrahigh dimensional variable selection through the penalized maximum trimmed likelihood estimator
The penalized maximum likelihood estimator (PMLE) has been widely used for variable selection in high-dimensional data. Various penalty functions have been employed for this purpose, e.g., Lasso, weighted Las...
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Article
Erratum to: Ultrahigh dimensional variable selection through the penalized maximum trimmed likelihood estimator
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Article
Robust second-order least-squares estimation for regression models with autoregressive errors
Rosadi and Peiris (Comput Stat 29:931–943, 2014) applied the second-order least squares estimator (SLS), which was proposed in Wang and Leblanc (Ann Inst of Stat Math 60:883–900, 2008), to regression models with ...
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Article
Open AccessClassical and Robust Regression Analysis with Compositional Data
Compositional data carry their relevant information in the relationships (logratios) between the compositional parts. It is shown how this source of information can be used in regression modeling, where the co...
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Article
Open AccessRobust logistic zero-sum regression for microbiome compositional data
We introduce the Robust Logistic Zero-Sum Regression (RobLZS) estimator, which can be used for a two-class problem with high-dimensional compositional covariates. Since the log-contrast model is employed, the ...