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ZüKoSt: Seminar on Applied Statistics

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Autumn Semester 2017

Date / Time Speaker Title Location
5 October 2017
16:15-17:00 		Christoph Stadtfeld
Department of Humanities, Social and Political Sciences
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ZueKoSt: Seminar on Applied Statistics

Title DYNAMIC NETWORK ACTOR MODELS: INVESTIGATING COORDINATION TIES THROUGH TIME
Speaker, Affiliation Christoph Stadtfeld, Department of Humanities, Social and Political Sciences
Date, Time 5 October 2017, 16:15-17:00
Location HG G 19.1
Abstract Important questions in the social sciences are concerned with the circumstances under which individuals, organizations, or states mutually agree to form social network ties. Examples of these coordination ties are found in such diverse domains as scientific collaboration, international treaties, and romantic relationships and marriage. This article introduces dynamic network actor models (DyNAM) for the statistical analysis of coordination networks through time. The strength of the models is that they explicitly address five aspects about coordination networks that empirical researchers will typically want to take into account: (1) that observations are dependent, (2) that ties reflect the opportunities and preferences of both actors involved, (3) that the creation of coordination ties is a two-sided process, (4) that data might be available in a time-stamped format, and (5) that processes typically differ between tie creation and dissolution (signed processes), shorter and longer time windows (windowed processes), and initial and repeated creation of ties (weighted processes). Two empirical case studies demonstrate the potential impact of DyNAM models: The first is concerned with the formation of romantic relationships in a high school over 18 months, and the second investigates the formation of international fisheries treaties from 1947 to 2010. Keywords social networks, coordination ties, time-stamped data, stochastic actor-oriented models, goldfish, longitudinal network models, relational event models, international cooperation, romantic ties, DyNAM
DYNAMIC NETWORK ACTOR MODELS: INVESTIGATING COORDINATION TIES THROUGH TIMEread_more
HG G 19.1
19 October 2017
16:15-17:00 		Juan Nieto
Department of Mechanical and Process Engineering, ETHZ
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ZueKoSt: Seminar on Applied Statistics

Title A review on SLAM: Past, Present and Open Problems
Speaker, Affiliation Juan Nieto, Department of Mechanical and Process Engineering, ETHZ
Date, Time 19 October 2017, 16:15-17:00
Location HG G 19.2
Abstract Robot localization is a key capability needed to enable truly autonomous mobile robots. In this talk we will describe the SLAM (Simultaneous Localization and Mapping) problem, which consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot (localization) moving within it. We will first present the different and necessary components of a prototypical SLAM system, from the sensor data through the data association and loop closure to the state estimator. Then, we discuss some of the classical approaches to SLAM and show what is now the de-facto standard formulation. During the talk we will cover a broad set of topics including robustness and scalability in long-term mapping, metric and semantic representations for mapping. Furthermore, we will delineate open challenges and new research issues, that deserve careful scientific investigation.
A review on SLAM: Past, Present and Open Problemsread_more
HG G 19.2
26 October 2017
16:15-17:00 		Anthony Unwin
Universität Augsburg, Institut für Interdisziplinäre Informatik
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ZueKoSt: Seminar on Applied Statistics

Title Understanding Potential Outliers using the O3 Plot
Speaker, Affiliation Anthony Unwin, Universität Augsburg, Institut für Interdisziplinäre Informatik
Date, Time 26 October 2017, 16:15-17:00
Location HG G 19.2
Abstract Outliers may be important, in error, or irrelevant, but they are tricky to identify and deal with. Whether a case is identified as an outlier depends on the other cases in the dataset, on the variables available, and on the criteria used. A case can stand out as unusual on one or two variables, while appearing middling on the others. If a case is identified as an outlier, it is useful to find out why. This talk discusses the O3 plot (Overview Of Outliers) for supporting outlier analyses. O3 plots show which cases are often identified as outliers, which are identified in single dimensions, and which are only identified in higher dimensions. They highlight which variables and combinations of variables may be affected by possible outliers. Applications include a demographic dataset for the Bundestag constituencies in Germany and a university ranking dataset.
Understanding Potential Outliers using the O3 Plotread_more
HG G 19.2
9 November 2017
16:15-17:00 		Field Chris
Dalhousie University
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ZueKoSt: Seminar on Applied Statistics

Title Modelling Microbial Data with Time, Treatment and/or Space Variation
Speaker, Affiliation Field Chris, Dalhousie University
Date, Time 9 November 2017, 16:15-17:00
Location HG G 19.1
Abstract This talk is motivated by issues arising from microbial oceanic data that biological researchers have been collecting to understand variation in response to environmental changes. The data typically consists of counts of OTU's (operational taxonomic units) from ocean samples varying either in time, treatment and/or space. At any given observation there will typically be at least 1000 OTU’s of potential interest. In particular I will describe some data arising from an experimental study of microbial organisms in the oceans to asses the effect of enhanced carbon loading. I will indicate briefly our approach to modelling the data to take into account both the experimental and temporal variation. In our view, an essential first step is to carry out dimension reduction via clustering based on the results of Poisson generalized linear models. Then we can carry out the tests for any significant experimental effect. In this data, it is likely that only a small subset of the OTU’s may show a response to the carbon loading. During the talk, it will be clear that there are still some unresolved statistical issues on which we welcome feedback. I  should note that although the data I have is from the ocean, similar issues will arise with microbial data coming from many other  environments such as the human gut.
Modelling Microbial Data with Time, Treatment and/or Space Variationread_more
HG G 19.1

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