ZüKoSt: Seminar on Applied Statistics

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Autumn Semester 2010

Date / Time

Speaker

Title

Location

* 30 September 2010
16:15-17:30

Thordis Thorarinsdottir
University Heidelberg

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ZüKoSt Zürcher Kolloquium über Statistik

Title	Does Bayes beat squinting?
Speaker, Affiliation	Thordis Thorarinsdottir, University Heidelberg
Date, Time	30 September 2010, 16:15-17:30
Location	HG G 19.2
Abstract	The theory of point processes offers a realistic class of models for many processes that arise in fields such as epidemiology, ecology, and geology. However, these models are often difficult to analyse and model selection methods have not been adequately investigated. The primary focus of existing model selection methodology aims to detect repulsion or aggregation in the point pattern. While this is an important first step in the modelling of the processes, there is now a need to directly compare different repulsion or aggregation models. In many applications, this is a vital step in the modelling procedure, as the different models lead to very different interpretation of the underlying physical processes. In this talk, I will discuss this issue for climate data and introduce a general Bayesian framework that allows for such comparisons to be naturally conducted while simultaneously performing parameter inference and out of sample prediction. Joint work with Peter Guttorp.

Does Bayes beat squinting?read_more

HG G 19.2

* 7 October 2010
16:15-17:30

Andrew Hector
Universität Zürich

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ZüKoSt Zürcher Kolloquium über Statistik

Title	Some Challenges from the Statistical Analysis of Ecological Data
Speaker, Affiliation	Andrew Hector, Universität Zürich
Date, Time	7 October 2010, 16:15-17:30
Location	HG G 19.2
Abstract	Traditionally, biology and biologists have not been heavily mathematical. However, many areas of modern biology, including ecology, are becoming increasingly sophisticated in their use of mathematics and statistics. In this talk I shall try and give an idea of some of the things community ecologists need to use statistics for. In the first part of the talk I shall take one of the hot topics in ecology over the last 10-20 years - the impact of biodiversity loss on ecosystem functioning and stability - and show how the research led us from traditional least squares linear models to more complex approaches including Generalized Linear Models, Mixed-Effects models and Bayesian multilevel models. In the second part of the talk I shall show how the analysis of plant growth has required us to get to grips with non-linear mixed-effects models and spawned collaboration with Microsoft Research on developing more mechanistic process-based models of plant growth implemented using MCMC techniques. The goal of my talk is to promote greater communication and collaboration between ecology and statistics, despite the mathematical barriers that many ecologists face.

Some Challenges from the Statistical Analysis of Ecological Dataread_more

HG G 19.2

* 4 November 2010
16:15-17:30

Stephan Stahlschmidt
Humboldt-Universität, Berlin

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ZüKoSt Zürcher Kolloquium über Statistik

Title	Graphical Models and Sex-related Homicides
Speaker, Affiliation	Stephan Stahlschmidt, Humboldt-Universität, Berlin
Date, Time	4 November 2010, 16:15-17:30
Location	HG G 19.2
Abstract	We present an investigation into the link between the age of an offender and the characteristics of a specific crime, namely sex-related homicides. The work provides insight into how the age of an offender affects the crime and in reverse, if knowledge of events at a crime scene could be exploited to predict the age of an unidentified offender. As general sociological and psychological theory on this specific type of crime (and the precise influence of the offender's age) is lacking and therefore no hypothesis could have been tested up until now, the technique applied is an explorative analysis of 252 cases of sex-related homicides, which have been transferred to one of the biggest existing data bases on this specific type of crime. In detail, graphical modelling was applied to learn the structure of the data and a Bayesian network was generated. This Bayesian network constitutes a data driven model on sex-related homicides and highlights influences of the offender's age on the crime.

Graphical Models and Sex-related Homicidesread_more

HG G 19.2

* 11 November 2010
16:15-17:30

Federico Ambrogi
Università degli Studi di Milano, Milan, Italy

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ZüKoSt Zürcher Kolloquium über Statistik

Title	Clinical useful measures for the study of competing risks in survival analysis
Speaker, Affiliation	Federico Ambrogi, Università degli Studi di Milano, Milan, Italy
Date, Time	11 November 2010, 16:15-17:30
Location	HG G 19.2
Abstract	In clinical studies where multiple events during patients follow-up are of interest, the analysis of the crude cumulative incidence (CCI) is used to support clinical decisions while the analysis of the cause specific hazard (CSH) provides information on the disease dynamics for biological hypotheses generation and follow-up planning. Treatment failure, as the event firstly occurring, may be due to causes having different clinical implications in planning therapeutic strategies. The interest is generally focused on some specific causes of failure. Since only one of them can be actually observed on each patient, the competing risks methodology is appropriate. In this context, the sub-distribution hazard model is applied to infer on the difference among crude cumulative incidences. However, inference on sub-distribution hazards are not directly interpretable from a clinical perspective. To assess treatment or covariate effects, measures of clinical impact based on crude cumulative incidence should be considered. In particular relative risks, excess of risks, relative risk reduction and number of patients needed to be treated are known to be useful to clinical practitioners. The aim of this work is to provide a straightforward approach to obtain point and interval estimates of the above measures, by resorting to the general framework of transformation models, through suitable link functions in presence of competing risks. In particular, the proposal of Klein and Andersen, based on pseudo-values, was considered as starting point. The baseline cumulative risk was estimated resorting to regression spline functions on time. Time-varying effects of covariates were tested through interaction with time functions. A literature data set on a controlled clinical trial on prostate cancer, using causes of death as end-points, was used for illustration. The critical aspects of competing risks analysis will be illustrated using a study of the impact of micrometastases on patients with unilateral breast cancer, classified as node negative at diagnosis, and who had undergone surgery with axillary lymph node dissection. In this situation the endpoint of interest is the subsequent development of distant metastases.

Clinical useful measures for the study of competing risks in survival analysisread_more

HG G 19.2

18 November 2010
16:15-17:30

Heiko Bailer
Clariden Leu AG, Zürich

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ZüKoSt Zürcher Kolloquium über Statistik

Title	A simple but effective application of statistics in finance
Speaker, Affiliation	Heiko Bailer, Clariden Leu AG, Zürich
Date, Time	18 November 2010, 16:15-17:30
Location	HG G 19.1
Abstract	Nowadays, traders and financial research and sales groups increasingly crunch numbers. However, more often than not, their models do not fit the underlying data. This results in money loosing investments and/or in models that are viewed not as useful by experienced practitioners. This talk shows what can go wrong right from the start and how the choice of simple statistical methods - that are in line with the desired outcome - can deliver very useful results. I will discuss fat-tail properties of financial time series and its implication on asset allocation. In particular, I will show through an example how a robust version of a statistical measure (Mahalanobis) helps to improve the risk adjusted return of a tactical asset allocation model.

A simple but effective application of statistics in financeread_more

HG G 19.1

25 November 2010
16:15-17:30

Simon Wood
University of Bath

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ZüKoSt Zürcher Kolloquium über Statistik

Title	GAMs, GAMMs and other penalized GLMs with mgcv in R
Speaker, Affiliation	Simon Wood, University of Bath
Date, Time	25 November 2010, 16:15-17:30
Location	HG G 19.1
Abstract	Generalized additive models (GAM) are generalized linear models where the linear predictor depends on smooth functions of covariates, and the smooth functions are the targets of inference. Generalized additive mixed models (GAMM) are the equivalent generalization of GLMMs. This talk will briefly outline the theoretical framework that allows reliable and efficient estimation and inference with such models in the R package mgcv, making the link between penalized likelihood, Bayesian and mixed model approaches. The types of smooth function that can be used as model components will then be illustrated, followed by examples illustrating the diverse range of models that fall within the scope of penalized GLMs.

GAMs, GAMMs and other penalized GLMs with mgcv in Rread_more

HG G 19.1

9 December 2010
16:15-17:30

Zaid Harchaoui
Researcher in the INRIA of Grenoble

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ZüKoSt Zürcher Kolloquium über Statistik

Title	Multiple Change-point Estimation with a Total Variation Penalty
Speaker, Affiliation	Zaid Harchaoui, Researcher in the INRIA of Grenoble
Date, Time	9 December 2010, 16:15-17:30
Location	HG G 19.1
Abstract	We propose a new approach for dealing with the estimation of the location of change-points in one-dimensional piecewise constant signals observed in white noise. Our approach consists in reframing this task in a variable selection context. We use a penalized least-square criterion with a ℓ1-type penalty for this purpose. We explain how to implement this method in practice by using the LARS/LASSO algorithm. We then prove that, in an appropriate asymptotic framework, this method provides consistent estimators of the change-points with an almost optimal rate. We nally provide an improved practical version of this method by combining it with a reduced version of the dynamic programming algorithm and we successfully compare it with classical methods.

Multiple Change-point Estimation with a Total Variation Penaltyread_more

HG G 19.1

Notes: events marked with an asterisk (*) indicate that the time and/or location are different from the usual time and/or location and if you want you can subscribe to the iCal/ics Calender.

Organisers: Peter Bühlmann, Reinhard Furrer, Leonhard Held, Markus Kalisch, Hansruedi Künsch, Marloes Maathuis, Martin Mächler, Werner Stahel, Sara van de Geer

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