Method We obtained peripheral blood and induced sputum from 21 asthma patients and defined two patient groups based on sputum eosinophilia (cut-off 3%). Eosinophils and neutrophils from blood and sputum were analysed by flow cytometry for expression of activation and degranulation markers. Data were analysed by both classical, non-parametric statistics and a more advanced multi-dimensional appr...

BACKGROUND There is currently no way to verify the quality of a multiple sequence alignment that is independent of the assumptions used to build it. Sequence alignments are typically evaluated by a number of established criteria: sequence conservation, the number of aligned residues, the frequency of gaps, and the probable correct gap placement. Covariation analysis is used to find putatively i...

New non-parametric regression procedures called BSML (Basis Selection from Multiple Libraries) are proposed in this paper for estimating a complex function by a linear combination of basis functions adaptively selected from multiple libraries. Different classes of basis functions are chosen to model various features of the function, e.g. truncated constants can model change points in the functi...

A new approach to the non-parametric spectral estimation on the basis of the Support Vector (SV) framework is presented. Two algorithms are derived for both uniform and non-uniform sampling. The relationship between the SV free parameters and the underlying process statistics is discussed. The application in two real data examples, the sunspot numbers and the Heart Rate Variability, shows the h...

A simulation study was conducted to address the issue of how purely additive (simple) genetic architecture might impact on the efficacy of parametric and non-parametric genomic prediction methods. For this purpose, we simulated a trait with narrow sense heritability h2= 0.3, with only additive genetic effects for 300 loci in order to compare the predictive ability of 14 more practically used ge...

MOTIVATION A primary objective of microarray studies is to determine genes which are differentially expressed under various conditions. Parametric tests, such as two-sample t-tests, may be used to identify differentially expressed genes, but they require some assumptions that are not realistic for many practical problems. Non-parametric tests, such as empirical Bayes methods and mixture normal ...

We present a novel characterization of the generalized family wise error rate: kFWER. The interpretation allows researchers to view kFWER as a function of the test statistics rather than current methods based on p-values. Using this interpretation we present several theorems and methods (parametric and non-parametric) for estimating kFWER in various data settings. With this version of kFWER, re...

In this paper, we consider both estimation and testing problems in a nonlinear time series model with nonstationarity. A nonparametric estimation method is proposed to estimate a sequence of nonparametric departure functions. We also propose a test statistic to test whether the regression function is of a known parametric nonlinear form. The power function of the proposed nonparametric test is ...

In this paper, we consider a nonparametric permutation test on the correlation coefficient, which is applied to a significance test on regression coefficients. Because the permutation test is very computerintensive, there are few studies on small-sample properties, although we have numerous studies on asymptotic properties with regard to various aspects. In this paper, we aim to compare the per...