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Multivariate plug-in bandwidth selection with unconstrained pilot bandwidth matrices
Multivariate kernel density estimation is an important technique in exploratory data analysis. Its utility relies on its ease of …
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On the probability of holes in truncated samples
For truncated data the existence of “holes” resp. inner risk sets may cause some problems when analyzing or applying the …
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Optimal rank-based testing for principal components
This paper provides parametric and rank-based optimal tests for eigenvectors and eigenvalues of covariance or scatter matrices in …
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Shifts in individual parameters of a GARCH model
Most asset return series, especially those in high frequency, show high excess kurtosis and persistence in volatility that cannot be …
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Testing for common principal components under heterokurticity
The so-called common principal components (CPC) model, in which the covariance matrices ${\Sigma}$ of m populations are assumed to have …
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The Gaussian mixture conditional correlation model: Parameter estimation, value at risk calculation and portfolio selection
A multivariate generalized autoregressive conditional heteroscedasticity model with dynamic conditional correlations is proposed, in …
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The statistical analysis of consecutive survival data under serial dependence
In the analysis of medical data, one often encounters data that are observed sequentially over time. For example in AIDS studies, let …
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Data-driven choice of the smoothing parametrization for kernel density estimators
There are several levels of sophistication when specifying the bandwidth matrix $\mathbf{H}$ to be used in a multivariate kernel …
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Integral distribution-free statistics of $L_p$-type and their asymptotic comparison
Generalizing the Cramér–von Mises and the Kolmogorov–Smirnov test, different integral statistics based on $L_p$-norms are compared with …
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Is it possible to test if a power of the density is integrable?
It is not clear what $L_p$-distance should be used to measure the error in density estimation. Whereas the $L_1$-distance makes sense …
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