Nonlinear and chaotic patterns in Japanese video game console sales and consequences for management control

This paper investigates the behaviour of weekly hardware sales in the Japanese video game sector. It is found that weekly hardware sales exhibit significant linear and non-linear behaviours during the product cycle. We are going to analyse the implications of our findings for management control in the video game sector.forecasting, marketing, time series, systems dynamics, chaos theory

Nonlinear and chaotic patterns in Japanese video game console sales and consequences for management control

This paper investigates the behaviour of weekly hardware sales in the Japanese video game sector. It is found that weekly hardware sales exhibit significant linear and non-linear behaviours during the product cycle. We are going to analyse the implications of our findings for management control in the video game sector

Can Zipf's law be adapted to normalize microarrays?

BACKGROUND: Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented. RESULTS: Using pairwise comparisons using MA plots (log ratio vs. log intensity), we compared this novel method to previously published normalization techniques, namely global normalization to the mean, the quantile method, and a variation on the loess normalization method designed specifically for boutique microarrays. Results indicated that, for single channel microarrays, the quantile method was superior with regard to eliminating intensity-dependent effects (banana curves), but Zipf's law normalization does minimize this effect by rotating the data distribution such that the maximal number of data points lie on the zero of the log ratio axis. For two channel boutique microarrays, the Zipf's law normalizations performed as well as, or better than existing techniques. CONCLUSION: Zipf's law normalization is a useful tool where the Quantile method cannot be applied, as is the case with microarrays containing functionally specific gene sets (boutique arrays)

Application of Benford's law in scientometrics

This diploma thesis is focused on determining the degree of presence of Benford's law in citation data. The data and their acquisition are described in detail. The most extensive analysis was performed on a dataset of 8.6 million records of scientific outputs from the Web of Science database, over a five-year period, with a selection of the three most numerous and most cited types of documents. Descriptive MAD (Mean Absolute Deviation) statistic were used to determine the degree of presence of Benford's law. The degree of presence of Benford's law was also determined for two datasets, the production of public universities in the Czech Republic and the Academy of Sciences of the Czech Republic under the same conditions as in other analyses.Tato diplomová práce je zaměřena na zjištění míry sledování Benfordova zákona v citačních datech. Detailně jsou popsána data i jejich získání. Nejrozsáhlejší analýza byla provedena nad datasetem 8,6 milionu záznamů vědeckých výstupů z databáze Web of Science, za pětileté období, s výběrem tří nejpočetnějších a nejcitovanějších typů dokumentů. Pro zjištění míry sledování Benfordova zákona byla použita popisná statistika MAD (Mean Absolute Deviation). Také byla zjištěna míra sledování Benfordova zákona u dvou datasetů, produkce veřejných vysokých škol České republiky a u Akademie věd České republiky a to za stejných podmínek, jako u dalších analýz.Ústav informačních studií a knihovnictvíInstitute of Information Studies and LibrarianshipFaculty of ArtsFilozofická fakult

Über Long-Tails, Mikroarrays, und Markersets: Integrative wissenschaftliche Ansätze in funktioneller Genomik, Populationsgenetik und genetischer Epidemiologie

The work in the three presented articles provides several demonstrations of how an integrative approach to scientific research has led to a better understand of biological phenomena. The first article incorporates research from the overlapping fields of biotechnology, functional genomics, and bioinformatics. The study's objective is to describe the nature of the distribution of gene expression levels measured with microarrays with the aim of developing an inter-array normalization method. The normalization method is compared to other existing normalization methods and is found to be especially suited to so-called boutique microarrays. The second article uses genotyping data generated by microarrays with the goal of examining the population genetic structure of the European human population. This study combines aspects of the fields of biotechnology, bioinformatics, and population genetics and sheds light on the genetic differences between Europeans by characterizing a strong correlation between geographic and genetic distance. In the final article, focus switches from genetic differences to genetic similarities in the same European individuals by examining the relationship structure of genetic nearest neighbors. Observations about these relationships lead to the proposal of a genetic matched-pair study design that contributes a methodological improvement to the field of genetic epidemiology. The proposed study design has the potential to increase the power of analysis of genome-wide association studies which are used to discover disease-causing genes. A presentation of previously unpublished research which was generated during the course of the work is also included. Finally, a discussion of long-tail data distributions initially observed in the first article leads to conclusions on the fundamental properties of the informational content of genetic marker sets ascertained in the last two articles.Die Arbeiten, die in den drei vorliegenden Artikeln präsentiert werden, zeigen, wie ein integrativer wissenschaftlicher Ansatz zu einem besseren Verständnis biologischer Phänomene führt. Der erste Artikel verknüpft Forschung aus den sich überlappenden Fachgebieten Biotechnologie, funktionelle Genomik und Bioinformatik. Das Ziel der Studie war es, mittels Mikroarrays die Verteilungsform der Genexpressionsniveaus zu bestimmen, um eine Normalisierungsmethode zu entwickeln. Diese Normalisierungsmethode wurde mit anderen bereits bekannten Normalisierungsmethoden verglichen und sie erwies sich als besonders geeignet für sogenannte Boutique-Mikroarrays. Der zweite Artikel verfolgt das Ziel, mit Hilfe von humanen Genotypisierungsdaten aus Mikroarrays die populationsgenetische Struktur der europäischen Population zu charakterisieren. Diese Studie verbindet Aspekte der Forschungsgebiete Biotechnologie, Bioinformatik und Populationsgenetik und gibt damit Aufschluss über die Muster genetischer Unterschiede zwischen Europäern: Es konnte eine hohe Korrelation zwischen geographischen und genetischen Distanzen gezeigt werden. Der letzte Artikel richtet den Blick auf die genetischen Gemeinsamkeiten der selben europäischen Individuen, indem er die Verwandtschaftsstruktur mittels eines genetischen "nearest neighbors"-Algorithmus untersucht. Die beobachteten Verwandtschaftsstrukturen führen zum Vorschlag eines genetischen Matched-Pair-Studiendesigns, das auf dem Gebiet der genetischen Epidemiologie eine erhebliche methodische Verbesserung darstellt. Das vorgeschlagene Studiendesign kann die Aussagekraft der statistischen Analysen bei Genom-weiten Assoziationsstudien erhöhen, also bei Studien, die durchgeführt werden, um krankheitsverursachende Gene zu identifizieren. Darüber hinaus werden bisher unveröffentlichte Forschungsergebnisse vorgestellt, die im Zusammenhang mit den obigen Studien gewonnen wurden. Eine abschließende Diskussion der Long-Tailed-Verteilung der Daten, die zunächst in der ersten Studie beobachtet wurde, führt zu Schlussfolgerungen über die grundlegenden Eigenschaften des Informationsgehaltes genetischer Markersets, welche nachfolgend in den letzten beiden Studien bestätigt wurden