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- Peter Hall, Spiridon I. Penev, Gerard Kerkyacharian, Dominique Picard
- Statistics and Computing
- 1997

PETER HALL, SPIRIDON PENEV, GEÃ‚ RARD KERKYACHARIAN and DOMINIQUE PICARD Centre for Mathematics and its Applications, Australian National University, Canberra, ACT 0200, Australia School of Mathematics, University of NSW, Sydney, NSW 2052, Australia FaculteÃ‚ Mathematiques et Informatiques, UniversiteÃ‚ de Picardie, 33 rue Saint-Leu, 80039 Amiens Cedex 01,â€¦ (More)

- Yanan Fan, Pierre Lafaye de Micheaux, Spiridon I. Penev, Donna Salopek
- J. Multivariate Analysis
- 2017

The problem of testing mutual independence of p random vectors in a general setting where the dimensions of the vectors can be different and the distributions can be discrete, continuous or both is of great importance. We propose such a test which utilizes multivariate characteristic functions and is a generalization of known results. We characterize theâ€¦ (More)

- Darinka Dentcheva, Spiridon I. Penev, Andrzej Ruszczynski
- Annals OR
- 2010

We derive representations of higher order dual measures of risk in Lp spaces as suprema of integrals of Average Values at Risk with respect to probability measures on (0, 1] (Kusuoka representations). The suprema are taken over convex sets of probability measures. The sets are described by constraints on the dual norms of certain transformations ofâ€¦ (More)

We suggest an adaptive sampling rule for obtaining information from noisy signals using wavelet methods. The technique involves increasing the sampling rate when relatively high-frequency terms are incorporated into the wavelet estimator, and decreasing it when, again using thresholded terms as an empirical guide, signal complexity is judged to haveâ€¦ (More)

- Tenko Raykov, Spiridon I. Penev
- The British journal of mathematical andâ€¦
- 2009

A procedure for point and interval estimation of maximal reliability of multiple-component measuring instruments in multi-level settings is outlined. The approach is applicable to hierarchical designs in which individuals are nested within higher-order units and exhibit possibly related performance on components of a given homogeneous scale. The method isâ€¦ (More)

- Spiridon I. Penev, Tenko Raykov
- Multivariate behavioral research
- 2006

A linear combination of a set of measures is often sought as an overall score summarizing subject performance. The weights in this composite can be selected to maximize its reliability or to maximize its validity, and the optimal choice of weights is in general not the same for these two optimality criteria. We explore several relationships between theâ€¦ (More)

Suppose we observe a geometrically ergodic Markov chain with a parametric model for the marginal, but no (further) information about the transition distribution. Then the empirical estimator for a linear functional of the joint law of two successive observations is no longer efficient. We construct an improved estimator and show that it is efficient. Theâ€¦ (More)

In many numerical examples it has been demonstrated that the saddlepoint approximation for the cumulative distribution function of a general nor-malised statistic behaves better in comparison with the third order Edge-worth expansion. The eeect is especially pronounced in the tails. Here we are dealing with the inverse problem of quantile evaluation. Theâ€¦ (More)

We suggest an adaptive sampling rule for obtaining information from noisy signals using wavelet methods. The technique involves increasing the sampling rate when relatively high-frequency terms are incorporated into the wavelet estimator, and decreasing it when, again using thresholded terms as an empirical guide, signal complexity is judged to haveâ€¦ (More)

- Tenko Raykov, Spiridon I. Penev
- The British journal of mathematical andâ€¦
- 2010

A procedure for testing mean collinearity in multidimensional spaces is outlined, which is applicable in settings with missing data and can be used when examining group mean differences. The approach is based on non-linear parameter restrictions and is developed within the framework of latent variable modelling. The method provides useful information aboutâ€¦ (More)