Statistical Modeling and Inference via Hierarchical Likelihood

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Description

The package provides a top interface of hierarchical likelihood (h-likelihood) based models. It currently covers the estimation of hierarchical generalized linear models (HGLMs) and frailty models.

Details

Package: h.likelihood
Type: Package
Version: 2010.9.20
Date: 2010-00-20
License: GPL
LazyLoad: yes
Depends: hglm, HGLMMM

Author(s)

Xia Shen, Marek Molas and Il Do Ha

Maintainer: Xia Shen <xia.shen@lcb.uu.se>

References

Ha, I.D. and Lee, Y. (2003). Estimating frailty models via Poisson Hierarchical generalized linear models. Journal of Computational and Graphical Statistics, 12, 663-681.

Ha, I.D. and Lee, Y. (2005). Comparison of hierarchical likelihood versus orthodox best linear unbiased predictor approaches for frailty models. Biometrika, 92, 717-723.

Ha, I.D., Lee, Y. and Song, J.-K. (2001). Hierarchical likelihood approach for frailty models. Biometrika, 88, 233-243.

Lee, Y. and Nelder, J.A. (1996). Hierarchical generalized linear models (with discussion). Journal of the Royal Statistical Society. Series B (Methological) 58, 619-678.

Lee, Y. and Nelder, J.A. (2001). Hierarchical generalised linear models: A synthesis of generalised linear models, random-effect models and structured dispersions. Biometrika 88, 987-1006.

Lee, Y., Nelder, J.A., and Pawitan, Y. (2006). Generalized Linear Models with Random Effects. Boca Raton: Chapman & Hall/CRC.

Molas, M. and Lesaffre, E. (2010). Hierarchical Generalized Linear Models: the R Package HGLMMM. Submitted.

Noh, M. and Lee, Y. (2007). REML estimation for binary data in GLMMs. Journal of Multivariate Analysis 98, 896-915.

Ronnegard, L., Shen, X. and Alam, M. (2010). hglm: A Package for Fitting Hierarchical Generalized Linear Models. The R Journal. (to appear)

See Also

hglm-package, HGLMMM-package