Information détaillée concernant le cours

Titre

École d’été 2018

Dates

02-05 Septembre 2018

Organisateur(s)

M. Yves Tillé, UNINE (Président) Mme Caroline Gillardin, UNINE (coordinatrice)

Intervenant(s)

Prof. Yoav Benjamini, Tel Aviv University (invité par l'EPFL) Prof. Claudia Czado, Technische Universität München Prof. Ingrid Van Keilegom, Katholieke Universiteit Leuven

 

Description

Professor Yoav Benjamini

(Tel Aviv University)

Title : Selective inference

will follow

Professor Claudia Czado

(Technische Universität München)

Title : Analyzing dependent data with vine copulas

This course is designed for graduate students and researchers who are interested in usingcopula based models for multivariate data structures. It provides a step to step introduction to the class of vine copulas and their statistical inference. This class of flexible copula models has become very popular in the last years for many applications in diverse fields such as finance, insurance, hydrology, marketing, engineering, chemistry, aviation, climatology and health.The popularity of vines copulas is due to the fact that it allows in addition to the separation of margins and dependence by the copula approach, tail asymmetries and separate multivariate component modeling. This is accommodated by constructing multivariate copulas using only bivariate building blocks which can be selected independently. These building blocks are glued together to valid multivariate copulas by appropriate condition-
ing. Thus also the term pair copula construction was coined by Aas et al. (2009). This approach allows for flexible and tractable dependence models in dimensions of several hundred, thus providing a long desired extension of the elliptical and Archimedean copula
classes. It forms the basis of new approaches in risk, reliability, spatial analysis, simulation,
survival analysis and data mining to name a few.

The course starts with background on multivariate and conditional distributions and copulas. Basic bivariate dependence measures are then introduced. Bivariate parametric classes of elliptical, Archimedean are then introduced and graphical tools for the identification of sensible bivariate copula models to data are developed. The decomposition and construction principle of vines is first given in three dimensions and then extended to the special cases of draw able (D-) and canonical (C-) vines. The general case of regular (R-) vines is developed. Simulation algorithms and parameter estimation methods will be constructed. Model selection methods for vine models are then considered. The short course closes with a case study characterizing the dependence among German assets contained in the DAX index. Computations are facilitated using the freely available package VineCopula of Schepsmeier et al. (2017) package in R (see R Core Team (2017)). Resources on vine models can be found under vine-copula.org

Professor Ingrid Van Keilegom

(Katholieke Universiteit Leuven)

Title : Survival analysis : from basic concepts to open research questions

In the first part of the course some basic concepts of survival analysis will be reviewed, like the concepts of right censoring and left truncation, some common parametric distribution functions in survival analysis, nonparametric estimation of basic quantities (Kaplan-Meier estimator of the survival distribution, Nelson-Aalen estimator of the cumulative hazard function,…), hypothesis testing regarding the equality of two or more survival curves, proportional hazards models, accelerated failure time models, etc.

The second part of the course will treat a number of more specific topics in survival analysis, that are in full development :

(1) Cure models : these are survival models used in situations where a certain proportion of the subjects under study are not susceptible to the event of interest (i.e. they have an infinite survival time). These models are of interest e.g. in cancer studies where one is interested in the time until recurrence of the cancer. Those individuals who are cured of their cancer will never have a relapse and will hence have an infinite event time. We will review some of the existing models and estimation methods in this context.

(2) Dependent censoring : Most models and methods in survival analysis assume that the survival time and the censoring time are independent random variables. This assumption is made for identifiability reasons, but is not satisfied in a number of practical situations. We will discuss how existing models can be adapted to take dependent censoring into account.

(3) Measurement errors : In survival analysis, as in many other areas of statistics, it often happens that explanatory variables in a regression model are measured with some error (e.g. blood pressure, weight, wage,…). Taking measurement errors into account is essential to do valid estimation and inference. We will review some of the existing models and methods for common regression models in survival analysis.

While the second part focusses on existing literature in the three stated sub-areas of survival analysis, the third part of the course will go one step further and will handle some of the open issues and research questions in these three areas. Since these areas are in full development, many aspects are still unexplored and worth investigating.

 Program (could be changed)

 

 

 
 

Sunday 02.09

 
 

Monday 03.09

 
 

Tuesday 04.09

 
 

Wednesday 05.09

 
 

 8h30-10h00

 
   

Ingrid Van Keilegom

 
 

Ingrid Van Keilegom

 
 

Ingrid Van Keilegom

 
 

10h00-10h30

 
 

 

 
 

Coffee Break

 
 

Coffee Break

 
 

Coffee Break

 
 

10h30-12h00

 
 

 

 
 

Claudia Czado

 
 

Claudia Czado

 
 

Claudia Czado

 
 

12h00-14h00

 
 

 

 
 

 

 
 

 

 
 

 

 
 

14h00-15h00

 
 

 

 
 

 Comité scientifique (13h30 à 15h30)

 
 

 

 
 

 

 
 

15h30-17h00

 
 

Welcome tea

 
 

Coffee Break

 
 

Coffee Break

 
 

 

 
 

17h00-18h30

 
 

Yoav Benjamini

 
 

Yoav Benjamini

 
 

Yoav Benjamini

 
 

18h30-19h30

 
 

Apero

 
 

 

 
 

 

 
 

19h30-21h00

 
 

Dinner

 
 

Dinner

 
 

Dinner

 

 

Lieu

Villars-sur-Ollon

Information
 Eurotel Victoria Villars
Route des Layeux, 1884 Villars-sur-Ollon (Tél +41 24 495 31 31)

Site Eurotel : http://www.eurotel-victoria.ch/villars/fr Accès à Villars :

  • EN VOITURE : Autoroute A9, direction Grand St-Bernard, sortie Aigle. Puis suivre les panneaux routiers « Ollon » puis « Villars ».

 

  • EN AVION : Aéroports internationaux de:

- Genève (120 km) ou Zürich (250 km) ou Bâle (200 km)
- puis EN TRAIN  (HORAIRE DES TRAINS - RAILWAY TIMETABLE)

  • EN TRAIN ET BUS : Suisse Train schedule : From: Geneve airport, To: Villars-sur-Ollon, gare. Trains directs jusqu'à Aigle. Ensuite bus 14429 (Aigle - Villars-sur-Ollon gare).

 

  • EN TRAIN : Suisse Train schedule : From: Geneve airport, To: Bex, gare. Trains directs jusqu'à Bex. Changer de train à Bex jusqu'à Villars.


Durée des trajets:
Lausanne - Aigle (30 minutes), Aigle - Villars-sur-Ollon (35 minutes). Visa pour la Suisse (Swiss Online Visa application) Météo en suisse (meteoswiss.admin.ch)

Frais

Doctorant CUSO chambre double: 200 CHF
Doctorant CUSO chambre simple: 350 CHF
Post-doctorant CUSO chambre double: 300 CHF
Post-doctorant CUSO chambre simple: 450 CHF
Professeur CUSO chambre double: 400 CHF
Professeur CUSO chambre simple: 550 CHF
Non CUSO universitaire chambre double: 850 CHF
Non CUSO universitaire chambre simple: 1000 CHF
Non CUSO privé chambre double: 1300 CHF
Non CUSO privé chambre simple: 1500 CHF Lors de votre inscription, merci de bien vouloir indiquer dans la zone commentaire si vous désirez une chambre simple, ou double et le nom de la personne avec qui vous souhaiteriez partager votre chambre. Dans le cas où rien n'est indiqué, une chambre simple sera réservée.

Inscription

Versement sur compte postal:

CUSO
CCP 12-1873-8
Neuchâtel
BIC : POFICHBEXXX
IBAN : CH0509000000120018738 Merci d'écrire votre nom lors du paiement. Thank you to write your name on the payment wording.

Places

48

Délai d'inscription 27.08.2018
short-url short URL

short-url URL onepage