Search results for "probability"
showing 10 items of 3417 documents
Bayesian analysis and design for comparison of effect-sizes
2002
Comparison of effect-sizes, or more generally, of non-centrality parameters of non-central t distributions, is a common problem, especially in meta-analysis. The usual simplifying assumptions of either identical or non-related effect-sizes are often too restrictive to be appropriate. In this paper, the effect-sizes are modeled as random effects with t distributions. Bayesian hierarchical models are used both to design and analyze experiments. The main goal is to compare effect-sizes. Sample sizes are chosen so as to make accurate inferences about the difference of effect-sizes and also to convincingly solve the testing of equality of effect-sizes if such is the goal.
Using mathematical morphology for unsupervised classification of functional data
2011
This paper is concerned with the unsupervised classification of functional data by using mathematical morphology. Different morphological operators are used to extract relevant structures of the functions (considered as sets through their subgraph representations). These operators can be considered as preprocessing tools whose outputs are also functional data. We explore some dissimilarity measures and clustering methods for the classification of the transformed data. Our approach is illustrated through a detailed analysis of two data sets. These techniques, which have mainly been used in image processing, provide a flexible and robust toolbox for improving the results in unsupervised funct…
Derived variables calculated from similar joint responses: some characteristics and examples
1995
Abstract A technique (Cox and Wermuth, 1992) is reviewed for finding linear combinations of a set of response variables having special relations of linear conditional independence with a set of explanatory variables. A theorem in linear algebra is used both to examine conditions in which the derived variables take a specially simple form and lead to reduced computations. Examples are discussed of medical and psychological investigations in which the method has aided interpretation.
Sobolev Extensions Via Reflections
2022
We show that certain extension results obtained by Maz’ya and Poborchi for domains with an outward peak can be realized via composition operators generated by reflections. We also study the case of the complementary domains. peerReviewed
Independent component analysis based on symmetrised scatter matrices
2007
A new method for separating the mixtures of independent sources has been proposed recently in [Oja et al. (2006). Scatter matrices and independent component analysis. Austrian J. Statist., to appear]. This method is based on two scatter matrices with the so-called independence property. The corresponding method is now further examined. Simple simulation studies are used to compare the performance of so-called symmetrised scatter matrices in solving the independence component analysis problem. The results are also compared with the classical FastICA method. Finally, the theory is illustrated by some examples. peerReviewed
The size of Simes’ global test for discrete test statistics
1999
Abstract To increase the power of the Bonferroni–Holm procedure several modified Bonferroni procedures have been proposed (for example, Hochberg, 1988. Biometrika 75, 800–802; Hommel, 1988. Biometrika 75, 383–386), which are based on Simes’ global test (Simes, 1986. Biometrika 73, 751–754). By several simulation studies which, in particular, considered multinormal test statistics, it has been suggested that the Simes test is a level α test. However, an exact proof exists for only few situations one of them assuming independence of test statistics. We studied the behaviour of Simes’ test for discrete test statistics. Due to discreteness one can expect more conservative decisions whereas depe…
Comparison of the Andersen–Gill model with poisson and negative binomial regression on recurrent event data
2008
Many generalizations of the Cox proportional hazard method have been elaborated to analyse recurrent event data. The Andersen-Gill model was proposed to handle event data following Poisson processes. This method is compared with non-survival approaches, such as Poisson and negative binomial regression. The comparison is performed on data simulated according to various event-generating processes and differing in subject heterogeneity. When robust standard error estimates are applied, for Poisson processes the Andersen-Gill approach is comparable to a negative binomial regression, whereas the poisson regression has comparable coverage probabilities of confidence intervals, but increased type …
Weighted bounded mean oscillation applied to backward stochastic differential equations
2015
Abstract We deduce conditional L p -estimates for the variation of a solution of a BSDE. Both quadratic and sub-quadratic types of BSDEs are considered, and using the theory of weighted bounded mean oscillation we deduce new tail estimates for the solution ( Y , Z ) on subintervals of [ 0 , T ] . Some new results for the decoupling technique introduced in Geiss and Ylinen (2019) are obtained as well and some applications of the tail estimates are given.
Block Based Deconvolution Algorithm Using Spline Wavelet Packets
2010
This paper presents robust algorithms to deconvolve discrete noised signals and images. The idea behind the algorithms is to solve the convolution equation separately in different frequency bands. This is achieved by using spline wavelet packets. The solutions are derived as linear combinations of the wavelet packets that minimize some parameterized quadratic functionals. Parameters choice, which is performed automatically, determines the trade-off between the solution regularity and the initial data approximation. This technique, which id called Spline Harmonic Analysis, provides a unified computational scheme for the design of orthonormal spline wavelet packets, fast implementation of the…
Optimal signed-rank tests based on hyperplanes
2005
Abstract For analysing k -variate data sets, Randles (J. Amer. Statist. Assoc. 84 (1989) 1045) considered hyperplanes going through k - 1 data points and the origin. He then introduced an empirical angular distance between two k -variate data vectors based on the number of hyperplanes (the so-called interdirections ) that separate these two points, and proposed a multivariate sign test based on those interdirections. In this paper, we present an analogous concept (namely, lift-interdirections ) to measure the regular distances between data points. The empirical distance between two k -variate data vectors is again determined by the number of hyperplanes that separate these two points; in th…