Dr. F. Dunker (University of Canterbury, Christchurch, New Zealand)
Wednesday, December 13, 2017 - 10:00
Weierstraß-Institut
Mohrenstr. 39, 10117 Berlin, Erhard-Schmidt-Hörsaal, Erdgeschoss
Forschungsseminar Mathematische Statistik
A popular way to model unobserved heterogeneity is the linear random coecient mo- del Y i = i;1Xi;1 + i;2Xi;2 + ::: + i;dXi;d. We assume that the observations (Xi; Yi); i = 1; :::; n, are i.i.d. where Xi = (Xi;1; :::;Xi;d) is a d-dimensional vector of regressors. The random coecients i = ( i;1; :::; i;d); i = 1; :::; n, are unobserved i.i.d. realizations of an unknown d-dimensional distribu- tion with density f independent of Xi. We propose and analyze a nonparametric multi-scale test for shape constraints of the random coecient density f . In particular we are interested in con dence sets for slopes and modes of the density. The test uses the connection between the model and the d-dimensional Radon transform and is based on Gaussian approximation of empirical processes. This is a joint work with K. Eckle, K. Proksch, and J. Schmidt-Hieber.
submitted by chschnei (christine.schneider@wias-berlin.de, 030 20372574)