Asymptotics of the two-stage spatial sign correlation

Acknowledgments This research was supported in part by the Collaborative Research Grant 823 of the German Research Foundation. The authors wish to thank the editors and referees for their careful handling of the manuscript. They further acknowledge the anonymous referees of the article Spatial sign correlation (J. Multivariate Anal. 135, pages 89–105, 2015), who independently of each other suggested to further explore the properties of two-stage spatial sign correlation.Non peer reviewedPreprin

Spatial Sign Correlation

A new robust correlation estimator based on the spatial sign covariance matrix (SSCM) is proposed. We derive its asymptotic distribution and influence function at elliptical distributions. Finite sample and robustness properties are studied and compared to other robust correlation estimators by means of numerical simulations.Comment: 20 pages, 7 figures, 2 table

The spatial sign covariance matrix and its application for robust correlation estimation

8 pages, 2 figures, to be published in the conference proceedings of 11th international conference "Computer Data Analysis & Modeling 2016" http://www.ajs.or.at/index.php/ajs/about/editorialPolicies#openAccessPolicyPeer reviewedPublisher PD

Robust change-point detection and dependence modeling

This doctoral thesis consists of three parts: robust estimation of the autocorrelation function, the spatial sign correlation, and robust change-point detection in panel data. Albeit covering quite different statistical branches like time series analysis, multivariate analysis, and change-point detection, there is a common issue in all of the sections and this is robustness. Robustness is in the sense that the statistical analysis should stay reliable if there is a small fraction of observations which do not follow the chosen model. The first part of the thesis is a review study comparing different proposals for robust estimation of the autocorrelation function. Over the years many estimators have been proposed but thorough comparisons are missing, resulting in a lack of knowledge which estimator is preferable in which situation. We treat this problem, though we mainly concentrate on a special but nonetheless very popular case where the bulk of observations is generated from a linear Gaussian process. The second chapter deals with something congeneric, namely measuring dependence through the spatial sign correlation, a robust and within the elliptic model distribution-free estimator for the correlation based on the spatial sign covariance matrix. We derive its asymptotic distribution and robustness properties like influence function and gross error sensitivity. Furthermore we propose a two stage version which improves both efficiency under normality and robustness. The surprisingly simple formula of its asymptotic variance is used to construct a variance stabilizing transformation, which enables us to calculate very accurate confidence intervals, which are distribution-free within the elliptic model. We also propose a positive semi-definite multivariate spatial sign correlation, which is more efficient but less robust than its bivariate counterpart. The third chapter deals with a robust test for a location change in panel data under serial dependence. Robustness is achieved by using robust scores, which are calculated by applying psi-functions. The main focus here is to derive asymptotics under the null hypothesis of a stationary panel, if both the number of individuals and time points tend to infinity. We can show under some regularity assumptions that the limiting distribution does not depend on the underlying distribution of the panel as long as we have short range dependence in the time dimension and ndependence in the cross sectional dimension

On the eigenvalues of the spatial sign covariance matrix in more than two dimensions

Acknowledgments Alexander Dürre was supported in part by the Collaborative Research Grant 823 of the German Research Foundation. David E. Tyler was supported in part by the National Science Foundation grant DMS-1407751. A visit of Daniel Vogel to David E. Tyler was supported by a travel grant from the Scottish Universities Physics Alliance. The authors are grateful to the editors and referees for their constructive comments.Non peer reviewedPostprin

Butanol production from lignocellulosic biomass: revisiting fermentation performance indicators with exploratory data analysis

After just more than 100 years of history of industrial acetone–butanol–ethanol (ABE) fermentation, patented by Weizmann in the UK in 1915, butanol is again today considered a promising biofuel alternative based on several advantages compared to the more established biofuels ethanol and methanol. Large-scale fermentative production of butanol, however, still suffers from high substrate cost and low product titers and selectivity. There have been great advances the last decades to tackle these problems. However, understanding the fermentation process variables and their interconnectedness with a holistic view of the current scientific state-of-the-art is lacking to a great extent. To illustrate the benefits of such a comprehensive approach, we have developed a dataset by collecting data from 175 fermentations of lignocellulosic biomass and mixed sugars to produce butanol that reported during the past three decades of scientific literature and performed an exploratory data analysis to map current trends and bottlenecks. This review presents the results of this exploratory data analysis as well as main features of fermentative butanol production from lignocellulosic biomass with a focus on performance indicators as a useful tool to guide further research and development in the field towards more profitable butanol manufacturing for biofuel applications in the future.publishedVersio

Production of propionate using metabolically engineered strains of Clostridium saccharoperbutylacetonicum

The carboxylic acid propionate is a valuable platform chemical with applications in various fields. The biological production of this acid has become of great interest as it can be considered a sustainable alternative to petrochemical synthesis. In this work, Clostridium saccharoperbutylacetonicum was metabolically engineered to produce propionate via the acrylate pathway. In total, the established synthetic pathway comprised eight genes encoding the enzymes catalyzing the conversion of pyruvate to propionate. These included the propionate CoA-transferase, the lactoyl-CoA dehydratase, and the acryloyl-CoA reductase from Anaerotignum neopropionicum as well as a D-lactate dehydrogenase from Leuconostoc mesenteroides subsp. mesenteroides. Due to difficulties in assembling all genes on one plasmid under the control of standard promoters, the PtcdB-tcdR promoter system from Clostridium difficile was integrated into a two-plasmid system carrying the acrylate pathway genes. Several promoters were analyzed for their activity in C. saccharoperbutylacetonicum using the fluorescence-activating and absorption-shifting tag (FAST) as a fluorescent reporter to identify suitable candidates to drive tcdR expression. After selecting the lactose-inducible PbgaL promoter, engineered C. saccharoperbutylacetonicum strains produced 0.7 mM propionate upon induction of gene expression. The low productivity was suspected to be a consequence of a metabolic imbalance leading to acryloyl-CoA accumulation in the cells. To even out the proposed imbalance, the propionate-synthesis operons were rearranged, thereby increasing the propionate concentration by almost four-fold. This study is the first one to report recombinant propionate production using a clostridial host strain that has opened a new path towards bio-based propionate to be improved further in subsequent work.publishedVersio

Butanol production from lignocellulosic biomass: revisiting fermentation performance indicators with exploratory data analysis

After just more than 100 years of history of industrial acetone–butanol–ethanol (ABE) fermentation, patented by Weizmann in the UK in 1915, butanol is again today considered a promising biofuel alternative based on several advantages compared to the more established biofuels ethanol and methanol. Large-scale fermentative production of butanol, however, still suffers from high substrate cost and low product titers and selectivity. There have been great advances the last decades to tackle these problems. However, understanding the fermentation process variables and their interconnectedness with a holistic view of the current scientific state-of-the-art is lacking to a great extent. To illustrate the benefits of such a comprehensive approach, we have developed a dataset by collecting data from 175 fermentations of lignocellulosic biomass and mixed sugars to produce butanol that reported during the past three decades of scientific literature and performed an exploratory data analysis to map current trends and bottlenecks. This review presents the results of this exploratory data analysis as well as main features of fermentative butanol production from lignocellulosic biomass with a focus on performance indicators as a useful tool to guide further research and development in the field towards more profitable butanol manufacturing for biofuel applications in the future