This paper provides parametric and rank-based optimal tests for eigenvectors and eigenvalues of covariance or scatter matrices in elliptical families. The parametric tests extend the Gaussian likelihood ratio tests of Anderson (1963) and their pseudo-Gaussian robustifications by Tyler (1981, 1983) and Davis (1977), with which their Gaussian versions are shown to coincide, asymptotically, under ...

statistical errors are common in scientific literature and about 50% of the published articles have at least one error. the assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. the aim of this commentary is to overview checking for normality in statistical analysis using spss.

Cognitive Science has typically proceeded with two major forms of research: model-building and experimentation. Traditional parametric statistics are normally used in the analysis of experiments, yet the assumptions required for parametric tests are almost never met in Cognitive Science. The purpose of this paper is twofold: to present a viable alternative to traditional parametric statistics—t...

trend analysis of changing stream flow of spring in khoramabad city in three times span namely month, season and annual were investigated by statistical method. the data used include data from 4spring were selected in 40-years period (1348-1388). in this study, the slope of the linear trend in the data sample estimates with using the tsa and then with using tfpwmethodthe effect of coefficient o...

In this paper we establish consistent tests of L2-type for the parametric functional form of the conditional mean of time series with values in Rd. A recent result on asymptotic distributions of U -statistics of weakly dependent observations is invoked to obtain the limit distributions of the test statistics. Since the asymptotic distributions depend on unknown parameters in a complicated way, ...

Two procedures are proposed for calculating standard errors for network statistics. Both are based on resampling of vertices: the first follows the bootstrap approach, the second the jackknife approach. In addition, we demonstrate how to use these estimated standard errors to compare statistics using an approximate t-test and how statistics can also be compared by another bootstrap approach tha...

Synthetic aperture radar (SAR) has a pivotal role as a remote imaging method. Obtained by means of coherent illumination, SAR images are contaminated with speckle noise. The statistical modelling of such contamination is well described according the multiplicative model and its implied G distribution. The understanding of SAR imagery and scene element identification is an important objective in...

This paper extends the Integrated Conditional Moment (ICM) test for the functional form of nonlinear regression models to tests for parametric conditional distributions. This test is formed on the basis of the integrated squared difference between the empirical characteristic function of the actual data and the characteristic function implied by the model. This test is consistent, and has nontr...

d t p d t A d n HE CHOICE OF STATISTICAL TEST HAS A PROFOUND impact on the interpretation of data. Understanding this choice is important for the critical evaluation of he biomedical literature. The question often arises hether to use nonparametric or parametric tests. The test is the most widely used statistical test for comparing he means of 2 independent groups. This parametric test ssumes t...

In this work, we show how permutation methods can be applied to combination analyses such as those that include multiple imaging modalities, multiple data acquisitions of the same modality, or simply multiple hypotheses on the same data. Using the well-known definition of union-intersection tests and closed testing procedures, we use synchronized permutations to correct for such multiplicity of...