Upcoming seminars

Friday, April 26, 15:15

Morten Overgaard
Aarhus Universitet
When do pseudo-observations have the appropriate conditional expectation?

A regression approach based on substituting observed and unobserved outcome values for pseudo-observations ought to work if the pseudo-observations have the appropriate conditional expectation. The pseudo-observations under study are jack-knife pseudo-values of some estimator and are closely related to the influence function of the estimator they are based on.

In this talk, we will have a look at some examples of such influence functions and look at potential problems and solutions concerning the conditional expectation. Specifically, influence functions from inverse probability of censoring weighted estimators where the estimate of the censoring distribution is allowed to take covariates into account and influence functions of the Kaplan–Meier estimator in a delayed entry setting will be considered.

Monday, May 06, 15:15

Benoit Liquet
Laboratory of Mathematics and their Applications, University of Pau and Pays de l’Adour
Variable Selection and Dimension Reduction methods for high dimensional and Big-Data Set

It is well established that incorporation of prior knowledge on the structure existing in the data for potential grouping of the covariates is key to more accurate prediction and improved interpretability.

In this talk, I will present new multivariate methods incorporating grouping structure in frequentist methodology for variable selection and dimension reduction to tackle the analysis of high dimensional and Big-Data set.

Map of CSS

You can find CSS next to the Botanical Garden, 5 minutes from Nørreport station.

Meeting room 5.2.46 is the library of the Biostatistics section, located in building 5, 2nd floor, room 46. See the map below for directions inside CSS.