We developed wavelet-based functional ANOVA (wfANOVA) as a novel approach for comparing neurophysiological signals that are functions of time. Temporal resolution is often sacrificed by analyzing such data in large time bins, increasing statistical power by reducing the number of comparisons. We performed ANOVA in the wavelet domain because differences between curves tend to be represented by a...

It is often of interest to undertake a general linear hypothesis testing (GLHT) problem in the one-way ANOVA without assuming the equality of the group variances. When the equality of the group variances is valid, it is well known that the GLHT problem can be solved by the classical F-test. The classical F test, however, may lead to misleading conclusions when the variance homogeneity assumptio...

The paper investigates a nonparametric regression method based on smoothing spline analysis of variance (ANOVA) approach to address the problem of global sensitivity analysis (GSA) of complex and computationally demanding computer codes. The two steps algorithm of this method involves an estimation procedure and a variable selection. The latter can become computationally demanding when dealing ...

The Analysis of Variance (ANOVA) is a commonly used statistical test in Statistics. The test compares the equality of means against the alternative that at least one of the means are different. In this report, we introduce a multivariate test known as Wavelet Analysis of Variance extending ANOVA to profile (functional) data. The test exploits the dimension reduction, noise elimination propertie...

This study focused on the influence of reading comprehension ability translation ability, and we classify based score into three categories they are low, moderate, high. The data analysis used statistical formula SPSS; tests were normality homogeneity tests. Hypothesis testing in this was carried out using a one-way variance (One Way ANova). finding there significant effect level translation. T...

A number of methods have been developed for modeling the evolution of a quantitative trait on a phylogeny. These methods have received renewed interest in the context of genome-wide studies of gene expression, in which the expression levels of many genes can be modeled as quantitative traits. We here develop a new method for joint analyses of quantitative traits within- and between species, the...

Symmetry and separability of spatial-temporal covariances are the main assumptions that are frequently taken for granted in most applications because of the simplicity of constructing covariance structure. However, many studies in environmental sciences show that real data have complex spatial-temporal dependency structures resulting from lack of symmetry or violation of other standard assumpti...