podcast.de
Anmeldung
Anmeldung Registrierung
Erweiterte Suche
  1. Startseite
  2. Podcasts
  3. Mathematik, Informatik und Statistik - Open Access LMU - Teil 01/03 Podcast
  4. Standard Errors for EM Estimates in Variance Component Models
A procedure is derived for computing standard errors in random
intercept models for estimates obtained from the EM algorithm. We
discuss two different approaches: a Gauss-Hermite quadrature for
Gaussian random effect models and a nonparametric maximum
likelihood estimation for an unspecified random effect
distribution. An approximation of the expected Fisher information
matrix is proposed which is based on an expansion of the EM
estimating equation. This allows for inferential arguments based on
EM estimates, as demonstrated by an example and simulations.

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