An EM algorithm for the estimation of parametric and nonparametric hierarchical nonlinear models
By Jeroen K. Vermunt. 2004
73 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/0ea0cf1b520cc3dd254f3e70f0b1d06526343900
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Jay Magidson
- Jeroen K. Vermunt
- Maria Iannario
- L. DeCarlo
- Jonas Edlund
- Alexandre J. S. Morin
- M. Porcu
- Francesca Giambona
In Statistics and Probability
- Jay Magidson
- Maria Iannario
- Jeroen K. Vermunt
- Karen Nylund-Gibson
- Katherine E. Masyn
- L. DeCarlo
- B. Muthén
- Zsuzsa Bakk
Citations in the corpus
- Hierarchical CUB Models for Ordinal Variables (2012, methodology): “In this article, a Gauss-Hermite quadrature routines have been applied (Bock and Atkin, 1981; Hedeker and Gibbons, 1996; Rabe-Hesketh et al., 2001; Stroud and Secrest, 1966; Vermunt, 2004).”
- Longitudinal Research Using Mixture Models (2010, methodology): “This yields what is referred to as a non-parametric maximum likelihood (NPML) approach to random effects modeling, which cannot only be used in the context of longitudinal data analysis but in any type of two-level regression model (Aitkin, 1999; Skrondal and Rabe-Hesketh, 2004; Vermunt 2004; Vermun”
- Technical Guide for Latent GOLD 5.1: Basic, Advanced, and Syntax 1 (2016, methodology): “Another application type of the Latent GOLD multilevel LC option is threelevel regression modeling (Vermunt, 2004).”
- Factor Analysis with Categorical Indicators: A Comparison Between Traditional and Latent Class Approaches (2005, methodology): “[INSERT FIGURE 1 ABOUT HERE] set is presented in Magidson and Vermunt (2004).”