Rank Reduction of Correlation Matrices by Majorization

A novel algorithm is developed for the problem of finding a low-rank correlation matrix nearest to a given correlation matrix. The algorithm is based on majorization and, therefore, it is globally convergent. The algorithm is computationally efficient, is straightforward to implement, and can handle arbitrary weights on the entries of the correlation matrix. A simulation study suggests that majorization compares favourably with competing approaches in terms of the quality of the solution within a fixed computational time. The problem of rank reduction of correlation matrices occurs when pricing a derivative dependent on a large number of assets, where the asset prices are modelled as correlated log-normal processes. Mainly, such an application concerns interest rates.rank, correlation matrix, majorization, lognormal price processes

Seriation by constrained correspondence analysis: a simulation study

One of the many areas in which Correspondence Analysis (CA) is an effectivemethod, concerns ordination problems. For example, CA is a well-knowntechnique for the seriation of archaeological assemblages. A problem withthe CA seriation solution, however, is that only a relative ordering of theassemblages is obtained. To improve the usual CA solution, a constrained CAapproach that incorporates additional information in the form of equalityand inequality constraints concerning the time points of the assemblages maybe considered. Using such constraints, explicit dates can be assigned to theseriation solution. In this paper, we extend the set of constraints that canbe used in CA by introducing interval constraints. That is, constraints thatput the CA\\ solution within a specific time-frame. Moreover, we study thequality of the constrained CA solution in a simulation study. In particular,by means of the simulation study we are able to assess how well ordinary andconstrained CA can recover the true time order. Furthermore, for theconstrained approach, we see how well the true dates are retrieved. Thesimulation study is set up in such a way that it mimics the data of a seriesof ceramic assemblages consisting of the locally produced tableware fromSagalassos (SW Turkey). We find that the dating of the assemblages on thebasis of constraints appears to work quite well.

Global Optimization strategies for two-mode clustering

Two-mode clustering is a relatively new form of clustering that clusters both rows and columns of a data matrix. To do so, a criterion similar to k-means is optimized. However, it is still unclear which optimization method should be used to perform two-mode clustering, as various methods may lead to non-global optima. This paper reviews and compares several optimization methods for two-mode clustering. Several known algorithms are discussed and a new, fuzzy algorithm is introduced. The meta-heuristics Multistart, Simulated Annealing, and Tabu Search are used in combination with these algorithms. The new, fuzzy algorithm is based on the fuzzy c-means algorithm of Bezdek (1981) and the Fuzzy Steps approach to avoid local minima of Heiser and Groenen (1997) and Groenen and Jajuga (2001). The performance of all methods is compared in a large simulation study. It is found that using a Multistart meta-heuristic in combination with a two-mode k-means algorithm or the fuzzy algorithm often gives the best results. Finally, an empirical data set is used to give a practical example of two-mode clustering.algorithms;fuzzy clustering;multistart;simulated annealing;simulation;tabu search;two-mode clustering

Pseudo-Jahn-Teller distortion of pyridine in its lowest triplet state

Biological and Soft Matter Physic

Review of the initial validation and characterization of a chicken 3K SNP array.

In 2004 the chicken genome sequence and more than 2.8 million single nucleotide polymorphisms (SNPs) were reported. This information greatly enhanced the ability of poultry scientists to understand chicken biology, especially with respect to identification of quantitative trait loci (QTL) and genes that control simple and complex traits. To validate and address the quality of the reported SNPs, assays for 3072 SNPS were developed and used to genotype 2576 DNAs isolated from commercial and experimental birds. Over 90% of the SNPs were valid based on the criterion used for segregating, and over 88% had a minor allele frequency of 2% or greater. As the East Lansing (EL) and Wageningen University (WAU) reference panels were genotyped, 1933 SNPs were added to the chicken genetic map, which was used in the second chicken genome sequence assembly. It was also discovered that linkage disequilibrium varied considerably between commercial layers and broilers; with the latter having haplotype blocks averaging 10 to 50 kb in size. Finally, it was estimated that commercial lines have lost 70% or more of their genetic diversity, with the majority of allele loss attributable to the limited number of chicken breeds used

Participatory plant breeding: a way to arrive at better-adapted onion varieties

The search for varieties that are better adapted to organic farming is a current topic in the organic sector. Breeding programmes specific for organic agriculture should solve this problem. Collaborating with organic farmers in such programmes, particularly in the selection process, can potentially result in varieties better adapted to their needs. Here, we assume that organic farmers' perceptive of plant health is broader than that of conventional breeders. Two organic onion farmers and one conventional onion breeder were monitored in their selection activities in 2004 and 2005 in order to verify whether and in which way this broader view on plant health contributes to improvement of organic varieties. They made selections by positive mass selection in three segregating populations under organic conditions. The monitoring showed that the organic farmers selected in the field for earliness and downy mildew and after storage for bulb characteristics. The conventional breeder selected only after storage. Farmers and breeder applied identical selection directions for bulb traits as a round shape, better hardness and skin firmness. This resulted in smaller bulbs in the breeders’ populations, while the bulbs in the farmer populations were bigger than in the original population. In 2006 and 2007 the new onion populations will be compared with each other and the original populations to determine the selection response

POSA: Perl Objects for DNA Sequencing Data Analysis

BACKGROUND: Capillary DNA sequencing machines allow the generation of vast amounts of data with little hands-on time. With this expansion of data generation, there is a growing need for automated data processing. Most available software solutions, however, still require user intervention or provide modules that need advanced informatics skills to allow implementation in pipelines. RESULTS: Here we present POSA, a pair of new perl objects that describe DNA sequence traces and Phrap contig assemblies in detail. Methods included in POSA include basecalling with quality scores (by Phred), contig assembly (by Phrap), generation of primer3 input and automated SNP annotation (by PolyPhred). Although easily implemented by users with only limited programming experience, these objects considerabily reduce hands-on analysis time compared to using the Staden package for extracting sequence information from raw sequencing files and for SNP discovery. CONCLUSIONS: The POSA objects allow a flexible and easy design, implementation and usage of perl-based pipelines to handle and analyze DNA sequencing data, while requiring only minor programming skills

More on Multidimensional Scaling and Unfolding in R: smacof Version 2

The smacof package offers a comprehensive implementation of multidimensional scaling (MDS) techniques in R. Since its first publication (De Leeuw and Mair 2009b) the functionality of the package has been enhanced, and several additional methods, features and utilities were added. Major updates include a complete re-implementation of multidimensional unfolding allowing for monotone dissimilarity transformations, including row-conditional, circular, and external unfolding. Additionally, the constrained MDS implementation was extended in terms of optimal scaling of the external variables. Further package additions include various tools and functions for goodness-of-fit assessment, unidimensional scaling, gravity MDS, asymmetric MDS, Procrustes, and MDS biplots. All these new package functionalities are illustrated using a variety of real-life applications

Effect of wetting layers on the strain and electronic structure of InAs self-assembled quantum dots

The effect of wetting layers on the strain and electronic structure of InAs self-assembled quantum dots grown on GaAs is investigated with an atomistic valence-force-field model and an empirical tight-binding model. By comparing a dot with and without a wetting layer, we find that the inclusion of the wetting layer weakens the strain inside the dot by only 1% relative change, while it reduces the energy gap between a confined electron and hole level by as much as 10%. The small change in the strain distribution indicates that strain relaxes only little through the thin wetting layer. The large reduction of the energy gap is attributed to the increase of the confining-potential width rather than the change of the potential height. First-order perturbation calculations or, alternatively, the addition of an InAs disk below the quantum dot confirm this conclusion. The effect of the wetting layer on the wave function is qualitatively different for the weakly confined electron state and the strongly confined hole state. The electron wave function shifts from the buffer to the wetting layer, while the hole shifts from the dot to the wetting layer.Comment: 14 pages, 3 figures, and 3 table