Robin Nunkesser

Hochschule Hamm-Lippstadt

Complex mobile applications require an appropriate global architecture. If used correctly, the high-level design patterns promoted by Apple and Google such as MVC, MVVM, and MVI/MVU may make an important contribution to the architecture, but they often require supplementary architectural concepts. General architectures such as Clean Architecture ma...

Complex mobile applications require an appropriate global architecture. If used correctly, the high-level design patterns promoted by Apple and Google such as MVC, MVVM, and MVI/MVU may make an important contribution to the architecture, but they often require supplementary architectural concepts. General architectures such as Clean Architecture ma...

Mobile Endgeräte und deren Software (Apps) haben es in einer beinahe beispiellosen Erfolgsgeschichte zu allgegenwärtigen Utensilien für Endnutzer gebracht. Im Controlling gibt es – trotz potentiellem Nutzen und deutlichem Interesse – noch keine weitverbreitete Nutzung von Apps. Im vorliegenden Kapitel werden Möglichkeiten mobiler Endgeräte und dere...

Currently, mobile operating systems are dominated by the duopoly of iOS and Android. App projects that intend to reach a high number of customers need to target these two platforms foremost. However, iOS and Android do not have an officially supported common development framework. Instead, different development approaches are available for multi-pl...

A drawback of robust statistical techniques is the increased computational effort often needed as compared to non-robust methods. Particularly, robust estimators possessing the exact fit property are NP-hard to compute. This means that—under the widely believed assumption that the computational complexity classes NP and P are not equal—there is no...

A fast update algorithm for online calculation of the Qn scale estimator is presented. This algorithm allows robust analysis of high-frequency time series in real time. It provides reliable estimates of a time-varying volatility even if many large outliers are present and it offers good efficiency in the case of clean Gaussian data.

Regression and classification are statistical techniques that may be used to extract rules and patterns out of data sets. Analyzing the involved algorithms comprises interdisciplinary research that offers interesting problems for statisticians and computer scientists alike. The focus of this thesis is on robust regression and classification in gene...

A drawback of robust statistical techniques is the increased computational effort often needed compared to non robust methods. Robust estimators possessing the exact fit property, for example, are NP-hard to compute. This means that — under the widely believed assumption that the computational complexity classes NP and P are not equal — there is no...

In this paper, the space requirements for the OBDD representation of certain graph classes, specifically cographs, several types of graphs with few P(4)s, unit interval graphs, interval graphs and bipartite graphs are investigated. Upper and lower bounds are proven for all these graph classes and it is shown that in most (but not all) cases a repre...

RFreak is an R package providing a framework for evolutionary computation. By enwrapping the functionality of an evolutionary algorithm kit written in Java, it offers an easy way to do evolutionary computation in R. In addition, application examples where an evolutionary approach is promising in computational statistics are included and described i...

In this paper a Genetic Programming algorithm for genetic association studies is reconsidered. It is shown, that the application field of the algorithm is not restricted to ge- netic association studies, but that the algorithm can also be applied to logic minimization problems. In the context of multi-valued logic minimization on incompletely speci...

Reliable automatic methods are needed for statistical online monitoring of noisy time series. Application of a robust scale estimator allows to use adaptive thresholds for the detection of outliers and level shifts. We propose a fast update algorithm for the Q n estimator and show by simulations that it leads to more powerful tests than other highl...

It is well-known that outliers cause severe problems when us- ing classical statistical approaches like ordinary least squares regression. Robust methods are to be preferred, but their application is hampered because of the high computational demands. In intensive care e.g., ro- bust regression techniques applied to a moving time window have been s...

Not individual single nucleotide polymorphisms (SNPs), but high-order interactions of SNPs are assumed to be responsible for complex diseases such as cancer. Therefore, one of the major goals of genetic association studies concerned with such genotype data is the identification of these high-order interactions. This search is additionally impeded b...

Motivation: Not individual single nucleotide polymorphisms (SNPs), but high-order interactions of SNPs are assumed to be responsible for complex diseases such as can- cer. Therefore, one of the major goals of genetic association studies concerned with such genotype data is the identification of these high-order interactions. This search is ad- diti...

A common problem in linear regression is that largely aberrant values can strongly influence the results. The least quartile difference (LQD) regression estimator is highly robust, since it can resist up to almost 50% largely deviant data values without becoming extremely biased. Additionally, it shows good behavior on Gaussian data – in contrast t...

A common problem in linear regression is that largely aberrant values can strongly influence the results. The least quartile difference (LQD) regression estimator is highly robust, since it can resist up to almost 50% largely deviant data values without becoming extremely biased. Additionally, it shows good behavior on Gaussian data – in contrast t...

In this paper, the space requirements for the OBDD representation of certain graph classes, specifically cographs, several types of graphs with few P 4s, unit interval graphs, interval graphs and bipartite graphs are investigated. Upper and lower bounds are proven for all these graph classes and it is shown that in most (but not all) cases a repres...

Least quartile difierence (LQD) regression is a highly robust method which possesses a breakdown point of 50%, i. e. it can resist up to almost 50% largely deviant data values without becoming extremely biased. Additionally, the Gaussian e卤ciency of the LQD estimator is 67:1% which is much higher than for most other robust regression estimators suc...

The analysis of genetic association is useful for identifying genetic fac- tors that may contribute to a medical condition. An important subarea are case- control studies on single nucleotide polymorphism (SNP) data, i.e. data on genetic variations that occur when different base alternatives exist at a single base pair position. The major goal of t...

Our main focus is on genetic association studies concerned with single nucleotide polymorphism (SNP) data, i.e. data on genetic variations that occur when different base alternatives exist at a single base pair position. Typical classification on this data aims at distinguishing between two groups, e.g. diseased subjects (cases) and healthy control...