Reduced-rank vector generalized linear models with two linear predictors

Computational Statistics and Data Analysis

Volumn 71, Issue , 2014, Pages 889-902

  Yee, Thomas W ^a  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

Author keywords

Generalized linear models; Negative binomial regression; Overdispersion; Reduced rank regression; Variance function; Zero inflated Poisson

Indexed keywords

GENERALIZED LINEAR MODEL; NEGATIVE BINOMIAL REGRESSION; OVERDISPERSION; REDUCED-RANK; VARIANCE FUNCTION; ZERO-INFLATED;

COMPUTATIONAL METHODS; DATA HANDLING;

REGRESSION ANALYSIS;

EID: 84889097516     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2013.01.012     Document Type: Article

References (38)

1. S.K. Ahn, and G.C. Reinsel Nested reduced-rank autoregressive models for multiple time series Journal of the American Statistical Association 83 403 1988 849 856
2. T.W. Anderson Estimating linear restrictions on regression coefficients for multivariate normal distributions Annals of Mathematical Statistics 22 3 1951 327 351
3. A.C. Cameron, and P.K. Trivedi Econometric models based on count data: comparisons and applications of some estimators and tests Journal of Applied Econometrics 1 1 1986 29 53
4. A.C. Cameron, and P.K. Trivedi Regression Analysis of Count Data 1998 Cambridge University Press Cambridge
5. R.J. Carroll, and D. Ruppert Transformation and Weighting in Regression 1988 Chapman and Hall New York, NY, USA
6. Dunn, P.K., 2012. tweedie: Tweedie exponential family models. R package version 2.1.5.
7. Dunn, P.K., Smyth, G.K., 2012. dglm: double generalized linear models. R package version 1.6.2. URL: http://CRAN.R-project.org/package=dglm.
8. M. Fiocco, H. Putter, and J.C. van Houwelingen Reduced rank proportional hazards model for competing risks Biostatistics 6 3 2005 465 478 (Pubitemid 41442763)
9. D.J. Fletcher Estimating overdispersion when fitting a generalized linear model to sparse data Biometrika 99 1 2012 230 237
10. A.S. Fullerton A conceptual framework for ordered logistic regression models Sociological Methods & Research 38 2 2009 306 347
11. W. Greene Functional forms for the negative binomial model for count data Economics Letters 99 3 2008 585 590
12. A. Heinen, and E. Rengifo Multivariate reduced rank regression in non-Gaussian contexts, using copulas Computational Statistics & Data Analysis 52 6 2008 2931 2944 (Pubitemid 351241281)
13. J.M. Hilbe Negative Binomial Regression second ed. 2011 Cambridge University Press Cambridge, UK, New York, USA
14. Hilbe, J.M., 2012. COUNT: functions, data and code for count data. R package version 1.2.3. URL: http://CRAN.R-project.org/package=COUNT.
15. A.J. Izenman Reduced-rank regression for the multivariate linear model Journal of Multivariate Analysis 5 2 1975 248 264
16. Jackman, S., 2012. pscl: classes and methods for R Developed in the Political Science Computational Laboratory, Stanford University. Department of Political Science, Stanford University, Stanford, California, USA, R package version 1.04.4. URL: http://pscl.stanford.edu/.
17. B. Jørgensen Exponential dispersion models Journal of the Royal Statistical Society: Series B 49 2 1987 127 162
18. C. Kleiber, and A. Zeileis Applied Econometrics with R 2008 Springer New York, NY, USA
19. Kneib, T., Heinzl, F., Brezger, A., Bove, D.S., 2011. BayesX: R utilities accompanying the software package BayesX. R package version 0.2-5. URL: http://CRAN.R-project.org/package=BayesX.
20. J.F. Lawless Negative binomial and mixed Poisson regression The Canadian Journal of Statistics 15 3 1987 209 225
21. S. Li, F. Yang, F. Famoye, C. Lee, and D. Black Quasi-negative binomial distribution: properties and applications Computational Statistics & Data Analysis 55 7 2011 2363 2371
22. Liu, H., Chan, K.-S., 2009. Constrained generalized additive models for zero-inflated data. Tech. Rep. 388, University of Iowa, IA, USA. URL: http://www.stat.uiowa.edu/sites/default/files/techrep/tr388-version2.pdf.
23. H. Liu, and K.-S. Chan Introducing COZIGAM: an R package for unconstrained and constrained zero-inflated generalized additive model analysis Journal of Statistical Software 35 11 2010 1 26 URL: http://www.jstatsoft.org/ v35/i11/
24. N.M. Neykov, P. Filzmoser, and P.N. Neytchev Robust joint modeling of mean and dispersion through trimming Computational Statistics & Data Analysis 56 1 2012 34 48
25. F.S.G. Richards A method of maximum-likelihood estimation Journal of the Royal Statistical Society. Series B. Methodological 23 2 1961 469 475
26. R.A. Rigby, and D.M. Stasinopoulos Generalized additive models for location, scale and shape, (with discussion) Applied Statistics 54 2005 507 554 (Pubitemid 40659551)
27. G.K. Smyth, A.F. Huele, and A.P. Verbyla Exact and approximate REML for heteroscedastic regression Statistical Modelling 1 3 2001 161 175
28. L.R. Taylor Aggregation, variance and the mean Nature 189 4766 1961 732 735
29. H. Turner, and D. Firth gnm: a package for generalized nonlinear models R News 7 2 2007 8 12 URL: http://CRAN.R-project.org/doc/Rnews/
30. W.N. Venables, and B.D. Ripley Modern Applied Statistics with S fourth ed. 2002 Springer New York 0-387-95457-0 URL: http://www.stats.ox.ac.uk/pub/ MASS4
31. J.M. Ver Hoef, and P.L. Boveng Quasi-Poisson vs. negative binomial regression: how should we model overdispersed count data? Ecology 88 11 2007 2766 2772 (Pubitemid 351345079)
32. R. Winkelmann, and K. Zimmermann Recent developments in count data modeling: theory and application Journal of Economic Surveys 9 1 1995 1 36
33. T.W. Yee A new technique for maximum-likelihood canonical Gaussian ordination Ecological Monographs 74 4 2004 685 701 (Pubitemid 40534053)
34. T.W. Yee Constrained additive ordination Ecology 87 1 2006 203 213 (Pubitemid 43363729)
35. T.W. Yee The VGAM package R News 8 2 2008 28 39 URL: http://CRAN.R- project.org/doc/Rnews/
36. T.W. Yee The VGAM package for categorical data analysis Journal of Statistical Software 32 10 2010 1 34 URL: http://www.jstatsoft.org/v32/i10/
37. T.W. Yee, and T.J. Hastie Reduced-rank vector generalized linear models Statistical Modelling 3 1 2003 15 41
38. A. Zeileis, C. Kleiber, and S. Jackman Regression models for count data in R Journal of Statistical Software 27 8 2008 1 25 URL: http://www.jstatsoft. org/v27/i08