Estimation in forest yield models using composite link functions with random effects

Biometrics

Volumn 53, Issue 1, 1997, Pages 146-160

  Candy, Steven G ^a  

^a FORESTRY TASMANIA   (Australia)

Author keywords

Composite link functions; Forest growth model; Generalized linear mixed models; Population averaged model; Random effects; Repeated measurements; Subject specific model

Indexed keywords

FORESTRY; POPULATION STATISTICS; RANDOM PROCESSES;

AVERAGED MODELS; COMPOSITE LINK FUNCTION; COMPOSITE LINKS; FOREST GROWTH MODEL; GENERALIZED LINEAR MIXED MODELS; LINK FUNCTIONS; POPULATION-AVERAGED MODEL; RANDOM EFFECTS; REPEATED MEASUREMENTS; SUBJECT SPECIFIC MODELING;

PARAMETER ESTIMATION;

ARTICLE; AVERAGE; FOREST; GROWTH; LINEAR SYSTEM; MEASUREMENT; NONHUMAN; POPULATION; RANDOMIZATION; STATISTICAL MODEL;

FOREST YIELD MODEL; GENERALIZED LINEAR MODEL; YIELD MODEL;

EID: 0030616951     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.2307/2533104     Document Type: Article

References (33)

1. Breslow, N. E. and Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 88, 9-25.
2. Breslow, N. E. and Lin, X. (1995). Bias correction in generalised linear mixed models with a single component of dispersion. Biometrika 82, 81-89.
3. Candy, S. G. (1989). Growth and yield models for Pinus radiata in Tasmania. New Zealand Journal of Forestry Science 19, 112-133.
4. Candy, S. G. (1991). Modeling insect phenology using ordinal regression and continuation ratio models. Environmental Entomology 20, 190-195.
5. Clutter, J. L., Fortson, J. C., Pienaar, L. V., Brister, G. H., and Bailey, R. L. (1983). Timber Management, a Quantitative Approach. New York: John Wiley & Sons.
6. Cox, C. (1984). Generalized linear models - The missing link. Applied Statistics 33, 18-24.
7. Cullis, B. R. and McGilchrist, C. A. (1990). A model for the analysis of growth data from designed experiments. Biometrics 46, 131-142.
8. Engel, B. and Keen, A. (1994). A simple approach for the analysis of generalized linear mixed models. Statistica Neerlandica 48, 1-22.
9. Garcia, O. (1994). The state-space approach in growth modelling. Canadian Journal of Forest Research 24, 1894-1903.
10. Genstat 5 Committee. (1993). Genstat 5 Reference Manual. Oxford: Clarendon Press.
11. Gregoire, T. G., Schabenberger, O., and Barrett, J. P. (1995). Modelling irregularly spaced, unbalanced, longitudinal data from permanent plot measurements. Canadian Journal of Forest Research 25, 137-156.
12. Harville, D. A. (1974). Bayesian inference for variance components using only error contrasts. Biometrika 61, 383-385.
13. Harville, D. A. (1977). Maximum likelihood approaches to variance component estimation and to related problems. Journal of the American Statistical Association 72, 320-340.
14. Jones, R. H. (1993). Longitudinal Data with Serial Correlation: A State-Space Approach. London: Chapman and Hall.
15. Lindstrom, M. J. and Bates, D. M. (1990). Nonlinear mixed effects models for repeated measures data. Biometrics 46, 673-687.
16. McCullagh, P. (1980). Regression models for ordinal data (with discussion). Journal of the Royal Statistical Society, Series B 42, 109-142.
17. McCullagh, P. and Neider, J. A. (1989). Generalized Linear Models, 2nd edition. London: Chapman and Hall.
18. McGilchrist, C. A. (1994). Estimation in generalized mixed models. Journal of the Royal Statistical Society, Series B 56, 61-69.
19. NAG. (1985). The GLIM System, Release 3.77. Oxford: NAG.
20. Nelder, J. A. and Pregibon, D. (1987). An extended quasi-likelihood function. Biometrika 74, 221-232.
21. Nelder, J. A. and Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society, Series A 135, 370-384.
22. Payne, R. W., Arnold, G. M., and Morgan, G. W. (eds). (1993). Genstat 5 Procedure Library Manual, Release 3[1]. Rothamsted Experimental Station, UK: Lawes Agricultural Trust.
23. Robinson, G . K. (1991). That BLUP is a good thing: The estimation of random effects. Statistical Science 6, 15-51.
24. Roger, J. H. (1983). Composite link functions with linear log link and Poisson error. GLIM Newsletter 7, 15-21.
25. Schabenberger, O. and Gregoire, T. G. (1995). A conspectus on estimating function theory and its application to recurrent modeling issues in forest biometry. Silva Fennica 29, 49-70.
26. Schall, R. (1991). Estimation in generalized linear models with random effects. Biometrika 78, 719-727.
27. Searle, S. R. (1965). Matrix Algebra for the Biological Sciences. London: John Wiley & Sons.
28. Speed, T. (1991). Comment on Robinson: Estimation of random effects. Statistical Science 6, 15-51.
29. Thompson, R. and Baker, R. J. (1981). Composite link functions in generalized linear models. Applied Statistics 30, 125-131.
30. Vonesh, E. F. and Carter, R. L. (1992). Mixed-effects nonlinear regression for unbalanced repeated measures. Biometrics 48, 1-17.
31. Wedderburn, R. W. M. (1974). Generalized linear models specified in terms of constraints. Journal of the Royal Statistical Society, Series B 36, 449-454.
32. Wolfinger, R. and O'Connell, M. (1993). Generalized linear mixed models: A pseudo-likelihood approach Journal of Statistical Computing and Simulation 48, 233-243.
33. Zeger, S. L., Liang, K. Y, and Albert, P. S. (1988). Models for longitudinal data: A generalized estimating equation approach. Biometrics 44, 1049-1060.