Semiparametric inference in generalized mixed effects models

By M. José Lombardía, Stefan Sperlich. 2008

60 citations recorded by the source corpus.

Subfields: Environmental Engineering, Nature and Landscape Conservation, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a2e94ca33ac9aa4b89ef4f6baaecc2bc9f0878c7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Wenceslao González-Manteiga
2. Jeffrey D. Hart
3. Gerda Claeskens
4. Rosa M. Crujeiras
5. Eduardo Garc'ia-Portugu'es

In Nature and Landscape Conservation

1. Wenceslao González-Manteiga
2. Jeffrey D. Hart
3. Gerda Claeskens

In Statistics and Probability

1. Gerda Claeskens
2. Jeffrey D. Hart
3. Wenceslao González-Manteiga
4. Rosa M. Crujeiras
5. Nils Lid Hjort
6. Xinyu Zhang
7. Hua Liang
8. Alan T. K. Wan

Citations in the corpus

• Goodness-of-fit tests in mixed models (2009, methodology): “While Verbeke and Lesaffre (1996) use the EM algorithm to estimate the unknown parameters, Proust and Jacqmin-Gadda (2005) use a Marquardt algorithm.”
• An updated review of Goodness-of-Fit tests for regression models (2013, background): “See also Lombardía and Sperlich (2008) for tests about m extending the works by Härdle et al. (1998) and Müller (2001) to the random effects context.”