Jan de Leeuw

1 The correlation matrix is of fundamental interest in many scientific studies that involve multiple variables, and the visualization of the correlation coefficient and the correlation matrix has b...

Turbidity currents commonly bypass sediment in submarine channels on the continental slope, and deposit sediment lobes farther down-dip on the flat and unconfined abyssal plain. Seafloor and outcrop data have shown that the transition from bypass to deposition usually occurs over complex zones referred to as channel–lobe transition zones (CLTZs). Recognition of these zones in cores and outcrop remains challenging due to a lack of characteristic sedimentary facies and structures. This paper focuses on Unit E of the Permian Fort Brown Formation in the Karoo Basin, South Africa, in the Slagtersfontein outcrop complex, which has previously been interpreted as a CLTZ. This study integrates thin-section micrographs, sedimentary facies, bed-set and stratigraphic architecture, and palaeoflow directions to achieve a multiscale analysis of CLTZ features. A novel process-based facies scheme is developed to evaluate deposits in terms of the depositional or erosional tendencies of the flows that formed them. This scheme allows bypass to be distinguished from depositional zones by the spatial distribution of certain sediment facies. Areas of net sediment bypass were predominantly marked by erosive sediment facies and a larger variability in palaeoflow direction while depositional areas showed a lower variability in palaeoflow directions. Metre-scale structures in the bypass-dominated area reveal seafloor erosion and scour formation. Field relations suggest the presence of a ∼500 m long mega-scour in the CLTZ. The characteristic structures documented here are applicable for identifying CLTZs in sparse datasets such as outcrops with limited palaeogeographical context and sediment cores obtained from subsurface systems.

When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show the methodology to be promising.

Twin studies are a major research direction in imaging genetics, a new field, which combines algorithms from quantitative genetics and neuroimaging to assess genetic effects on the brain. In twin imaging studies, it is common to estimate the intraclass correlation (ICC), which measures the resemblance between twin pairs for a given phenotype. In this paper, we extend the commonly used Pearson correlation to a more appropriate definition, which uses restricted maximum likelihood methods (REML). We computed proportion of phenotypic variance due to additive (A) genetic factors, common (C) and unique (E) environmental factors using a new definition of the variance components in the diffusion tensor-valued signals. We applied our analysis to a dataset of Diffusion Tensor Images (DTI) from 25 identical and 25 fraternal twin pairs. Differences between the REML and Pearson estimators were plotted for different sample sizes, showing that the REML approach avoids severe biases when samples are smaller. Measures of genetic effects were computed for scalar and multivariate diffusion tensor derived measures including the geodesic anisotropy (tGA) and the full diffusion tensors (DT), revealing voxel-wise genetic contributions to brain fiber microstructure.

The Journal of Statistical Software is an e‐journal that publishes and reviews open source statistical software. We discuss the history, motivation, and implementation of the journal. Copyright © 2009 John Wiley & Sons, Inc.This article is categorized under: Applications of Computational Statistics > Organizations and Publications

We review three decades of research linking social network methods with world systems theory. We identify four themes nested within two versions of a general social network methodology—the identification of network Roles and Position. The themes vary by the type of data and the definition of equivalence used to identify roles and positions. Second, we provide a demonstration of the general methodological approach taken in the literature, applying a recent methodological innovation to a newly compiled large global trade dataset. The results identify the expected core/periphery interaction pattern, suggesting that it is a fundamental feature of cross-national trade data, regardless of how the data are analyzed. We conclude by suggesting both methodological and substantive directions for future social network research on the world-system.

Multidimensional Scaling Using Majorization: SMACOF in R