Published in Annals of Operations Research
Cluster analysis is an unsupervised learning technique for partitioning objects into several clusters. Assuming that noisy objects are included, we propose a soft clustering method which assigns objects that are significantly different from noise into one of the specified number of clusters by controlling decision errors through multiple testing. T...
Prediction of physical particular phenomenon is based on knowledges of the phenomenon. Theses knowledges help us to conceptualize this phenomenon throw different models. Hidden Markov Models (HMM) can be used for modeling complex processes.We use this kind of models as tool for fault diagnosis systems. Nowadays, industrial robots living in stochast...
Published in Statistical Applications in Genetics and Molecular Biology
In this paper we establish the statistical properties of SGoF multitesting method under a mixture model. It is assumed that the available set of p-values is statistically independent. Special attention is paid to the huge dimension problem in which the number of tests goes to infinity. Formulae for the power and the rate of false discoveries/non-di...
Published in Metrika
Two hypothesis testing problems are considered in this paper to check the constancy of the coefficients in the varying-coefficient regression model. Tests for the two corresponding hypothesis testing problems are derived by two p-values. The proposed p-values can be thought as the generalized p-values, which are given by linear interpolation based ...
Published in Deutsches Ärzteblatt international
P-values in scientific studies are used to determine whether a null hypothesis formulated before the performance of the study is to be accepted or rejected. In exploratory studies, p-values enable the recognition of any statistically noteworthy findings. Confidence intervals provide information about a range in which the true value lies with a cert...
Published in Statistical Methods and Applications
The present paper considers two-sample tests for scale problem under symmetry without any assumption regarding the equality of medians. Two adaptive procedures are proposed—one is probabilistic while the other is deterministic. The proposed probabilistic approach is shown, by simulation studies, to maintain its significance level for various symmet...
Published in Statistics in medicine
Simon's 'optimal' and 'minimax' two-stage designs are common methods for conducting phase IIA studies investigating new cancer therapies. However, these designs are rather rigid in their settings because of the pre-specified rejection rules and fixed sample sizes at each stage. In practice, we often encounter the problem that a study is unable to a...
Published in Metrika
In an one-way analysis of variance with standard assumptions suppose that only one observation exists per treatment. In addition, assume that one of the treatments is a control group. Because of insufficient observations, the variance of the populations cannot be estimated and hence the usual methods for comparing treatments with the control group ...
Published in Journal of proteome research
The development of liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has made it possible to characterize phosphopeptides in an increasingly large-scale and high-throughput fashion. However, extracting confident phosphopeptide identifications from the resulting large data sets in a similar high-throughput fashion remains diffic...
The original Studentization was the conversion of a sample mean departure into the familiar t-statistic, plus the derivation of the corresponding Student distribution function; the observed value of the distribution function is the observed p-value, as presented in an elemental form. We examine this process in a broadly general context: a null stat...
