The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Computing Gaussian Likelihoods and Their Derivatives for General Linear Mixed Models
Abstract
Algorithms are described for computing the Gaussian likelihood or restricted likelihood corresponding to a general linear mixed model. Included are arbitrary covariance structures for both the random effects and errors. Formulas are also given for the first and second derivatives of the likelihoods, thus enabling a Newton–Raphson implementation. The algorithms make heavy use of the Cholesky decomposition, the sweep operator, and the W-transformation. Also described are the modifications needed for variance profiling, Fisher scoring, and MIVQUE(0), as well as the computational order of the procedures.
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Cites
Random-Effects Models for Longitudinal Data
Laird, N. M., & Ware, J. H. (1982) · Biometrics · doi:10.2307/2529876 · Cited by 8,923
Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
Harville, D. A. (1977) · Journal of the American Statistical Association · doi:10.1080/01621459.1977.10480998 · Cited by 2,667
Searle, S. R., Casella, G., & McCulloch, C. E. (1992) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316856 · Cited by 1,926
Cited by
(2004) · Springer Texts in Statistics · doi:10.1007/b98963 · Cited by 517
Wavelet-based Functional Mixed Models
Morris, J. S., & Carroll, R. J. (2006) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2006.00539.x · Cited by 396
Analyzing genotype-environment data by mixed models with multiplicative terms
Piepho, H.-P. (1997) · Biometrics · doi:10.2307/2533976 · Cited by 234
Metadata
- Authors
- Wolfinger, R., Tobias, R., & Sall, J.
- Venue
- SIAM Journal on Scientific Computing
- Published
- 1994-11
- Volume
- 15
- Issue
- 6
- Pages
- 1294-1310
- ISSN
- 1064-8275 (ISSN-L)
- 1095-7197
- OpenAlex
- W1997558610
- Cited by
- 169
- References
- 3
- FWCI
- 2.49
- Type
- journal article
- Language
- en
- Open access
- closed
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