podcast.de
Anmeldung
Anmeldung Registrierung
Erweiterte Suche
  1. Startseite
  2. Podcasts
  3. Mathematik, Informatik und Statistik - Open Access LMU - Teil 01/03 Podcast
  4. Smoothing Hazard Functions and Time-Varying Effects in Discrete Duration and Competing Risks Models
State space or dynamic approaches to discrete or grouped duration
data with competing risks or multiple terminating events allow
simultaneous modelling and smooth estimation of hazard functions
and time-varying effects in a flexible way. Full Bayesian or
posterior mean estimation, using numerical integration techniques
or Monte Carlo methods, can become computationally rather demanding
or even infeasible for higher dimensions and larger data sets.
Therefore, based on previous work on filtering and smoothing for
multicategorical time series and longitudinal data, our approach
uses posterior mode estimation. Thus we have to maximize posterior
densities or, equivalently, a penalized likelihood, which enforces
smoothness of hazard functions and time-varying effects by a
roughness penalty. Dropping the Bayesian smoothness prior and
adopting a nonparametric viewpoint, one might also start directly
from maximizing this penalized likelihood. We show how Fisher
scoring smoothing iterations can be carried out efficiently by
iteratively applying linear Kalman filtering and smoothing to a
working model. This algorithm can be combined with an EM-type
procedure to estimate unknown smoothing- or hyperparameters. The
methods are applied to a larger set of unemployment duration data
with one and, in a further analysis, multiple terminating events
from the German socio-economic panel GSOEP.

Weitere Episoden

Quantifying overdispersion effects in count regression data

Quantifying overdispersion effects in count regression data

vor 24 Jahren
Graphical chain models for the analysis of complex genetic diseases: an application to hypertension

Graphical chain models for the analysis of complex genetic diseases: an application to hypertension

vor 24 Jahren
Geo-additive models of Childhood Undernutrition in three Sub-Saharan African Countries

Geo-additive models of Childhood Undernutrition in three Sub-Saharan African Countries

vor 24 Jahren
Parametric and Nonparametric Regression with Missing X's - A Review

Parametric and Nonparametric Regression with Missing X's - A Review

vor 24 Jahren
A Selection Model for Bivariate Normal Data, with a Flexible Nonparametric Missing Model and a Focus on Variance Estimates

A Selection Model for Bivariate Normal Data, with a Flexible Nonparametric Missing Model and a Focus on Variance Estimates

vor 24 Jahren
Alle Episoden anzeigen
In Podcasts werben
Schalte jetzt Werbung in Podcasts.

Abonnenten

Teilen