Graphical games describe strategic interactions among a specified network of players. The threshold protocol game is a graphical game that models the adoption of a lesser-used product in a population when individuals benefit by using the same product. The threshold protocol game has historically...

The threshold protocol game is a graphical game that models the adoption of an idea or product through a population. There are two states players may take in the game, and the goal of the game is to motivate the state that begins in the minority to spread to every player. Here, the threshold...

The communities in a network have distinct characteristics and interrelationships. Community discovery methods based on node embedding and deep learning have surpassed spectral clustering and statistical inference as the preferred methods for handling high-dimensional network data. Community...

A time series can often be characterized using machine learning techniques, which require feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized machine learning techniques. We propose a method for combining features extracted from two popular...

Ziel der vorliegenden Webscraping-Analyse ist es, für die Betriebs- und Organisationslandschaft der Region Hannover sowie der Landkreise Hildesheim und Peine einen Überblick über die Relevanz innovativer Technologien und Konzepte zu geben. Hierfür werden die Websites ausgewertet und die...

Despite the widespread use of graphs in empirical research, little is known about readers' ability to process the statistical information they are meant to convey ("visual inference"). We study visual inference within the context of regression discontinuity (RD) designs by measuring how...

A frequent challenge when using graphical models in applications is that the sample size is limited relative to the number of parameters to be learned. Our motivation stems from applications where one has external data, in the form of networks between variables, that provides valuable...

We propose a way to formalize the relationship between descriptive analysis and structural estimation. A researcher reports an estimate ĉ of a structural quantity of interest c that is exactly or asymptotically unbiased under some base model. The researcher also reports descriptive statistics...

In recent years, graphics have become an essential part of modern data analysis. This paper describes a system called CLOUDS which is designed to make available on inexpensive storage tube terminals a wide range of graphic tools related to data analysis, economics, and management science. The...

We present a novel technique for cardinality-constrained index-tracking, a common task in the financial industry. Our approach is based on market graph models. We model our reference indices as market graphs and express the index-tracking problem as a quadratic K-medoids clustering problem. We...

Innere Kündigung ist ein vielseitig diskutiertes und dennoch empirisch kaum untersuchtes Phänomen. Aus den wenigen Arbeiten, die das Phänomen systematisch untersuchen, konnte sich keine Operationalisierung konsequent etablieren. Daher sollte in dieser Arbeit eine Skala entwickelt werden, die...

Despite the widespread use of graphs in empirical research, little is known about readers' ability to process the statistical information they are meant to convey ("visual inference"). We study visual inference within the context of regression discontinuity (RD) designs by measuring how...

Kenntnisse der Deskriptiven Statistik gehören für Studierende der Wirtschafts- und Sozialwissenschaften zum wichtigen Handwerkszeug. Auf kompakte Art und Weise stellt diese 3., überarbeitete und erweiterte Auflage die relevanten Fachtermini vor und vermittelt das Wichtigste zur Verteilung,...

Let G= (V, E) be a graph with p vertices and q edges. A graph G={V, E} with p vertices and q edges is said to be a Permutation labelling graph if there exists a bijection function f from set of all vertice G( ) to {1, 2,3... }p such that the induced edge labelling function h E G N : ( ) → is...

We propose a way to formalize the relationship between descriptive analysis and structural estimation. A researcher reports an estimate ĉ of a structural quantity of interest c that is valid under some model. The researcher also reports descriptive statistics ˆγ that estimate features γ of...

In this paper, we show that using multiple models when executing a specific task almost unavoidably gives rise to interaction between them, especially when their number is large. We show that this interaction can lead to biased and incomplete results if treated inappropriately (which we believe...

We apply a machine-learning algorithm calibrated from general human vision to predict visual salience of parts of a stock price series. We hypothesize that visual salience of adjacent prices increases decision weights on returns computed from those prices. We analyze the inferred decision impact...

In many domains we have witnessed the need to search a large entity-relation graph for direct and indirect relationships between a set of entities specified in a query. A search result, called a semantic association (SA), is typically a compact (e.g., diameter-constrained) connected subgraph...

This work presents the rationale of multidimensional coordinate systems as the most effective visual tool to understand the behavior of any natural phenomenon from a multidimensional perspective. The main motivation behind the creation of multidimensional coordinate systems is to propose an...

This paper deals with estimating model parameters in graphical models. We reformulate it as an information geometric optimization problem and introduce a natural gradient descent strategy that incorporates additional meta parameters. We show that our approach is a strong alternative to the...