Journal of Statistics: Advances in Theory and Applications
EXPERIMENTS WITH BETA RESPONSE[1] M. J. Bayarri and J. O. Berger, The interplay of Bayesian and
frequentist analysis, Statistical Sciences 19 (2004), 58-80.
[2] J. M. Bernardo and A. F. Smith, Bayesian Theory, John Wiley and
Sons Inc., Wiltshire, Great Britain, 2000.
[3] G. E. P. Box, W. G. Hunter and J. S. Hunter, Statistics for
Experimenters, John Wiley and Sons Inc., New Jersey, USA, 2005.
[4] A. J. Branscum, W. O. Johnson and M. C. Thurmond, Bayesian beta
regression: Applications to household expenditure data and genetic
distance between foot-and-mouth disease viruses, Australian and New
Zealand Journal of Statistics 3 (2007), 287-301.
[5] B. P. Carlin and T. A. Louis, Bayesian Methods for Data Analysis,
CRC Press, Boca Raton, Florida, USA, 2009.
[6] F. Cribari-Neto and A. Zeileis, Beta regression in R. Journal of
Statistical Software 2 (2010), 1-24.
[7] H. Eves, Elementary Matrix Theory, Dover Publications Inc., New
York, USA, 1980.
[8] S. L. P. Ferrari and F. Cribari-Neto, Beta regression for
modelling rates and proportions, Journal of Applied Statistics 31
(2004), 799-815.
[9] J. I. Figueroa-Zúniga, R. B. Arellano-Valle and S. L. P.
Ferrari, Mixed beta regression: A Bayesian perspective, Preprint, 2,
arXiv:1201.2375v2 (2012).
[10] B. Grün, I. Kosmidis and A. Zeileis, Extended beta regression
in R: Shaken, stirred, mixed, and partitioned, Journal of Statistical
Software 2 (2011), 1-24.
[11] R. Kieschnick and B. D. McCullough, Regression analysis of
variates observed on (0, 1): Percentages, proportions and fractions,
Statistical Modelling 3 (2003), 193-213.
[12] J. K. Kruschke, Doing Bayesian Data Analysis: A Tutorial with R
and BUGS, Academic Press, Burlington, USA, 2011.
[13] S. L. Lewis, D. C. Montgomery and R. H. Myers, Examples of
designed experiments with nonnormal responses, Journal of Quality
Technology 3 (2001a), 265-278.
[14] S. L. Lewis, D. C. Montgomery and R. H. Myers, Confidence
interval coverage for designed experiments analyzed with GLM, Journal
of Quality Technology 3 (2001b), 279-292.
[15] O. O. Melo, L. A. López and S. E. Melo, Diseno de Experimentos
(métodos y aplicaciones), Universidad Nacional de Colombia,
Bogotá, Colombia, 2007.
[16] D. C. Montgomery, Design and Analysis of Experiments, John Wiley
and Sons Inc., New Jersey, USA, 2005.
[17] D. C. Montgomery, E. A. Peck and G. G. Vining, Introduction to
Linear Regression Analysis, John Wiley and Sons Inc., New Jersey, USA,
2006.
[18] R. H. Myers and D. C. Montgomery, A tutorial on generalized
linear models, Journal of Quality Technology 29 (1997), 274-291.
[19] P. Paolino, Maximum likelihood estimation of models with
beta-distributed dependent variables, Political Analysis 9 (2001),
325-346.
[20] S. C. Patil and H. V. Kulkarni, Analysis of 2nd factorial
experiments with exponentially distributed response, Applied
Mathematical Sciences 10 (2011), 459-476.
[21] C. P. Robert and G. Casella, Monte Carlo Statistical Methods,
Springer, New York, USA, 2004.
[22] G. E. Shilov, Elementary Real and Complex Analysis, Dover
Publications Inc., New York, USA, 1973.
[23] M. Smithson and J. Verkuilen, A better lemon-squeezer? Maximum
likelihood regression with beta-distributed dependent variables,
Psychological Methods 11 (2006), 54-71.
[24] K. L. P. Vasconcellos and F. Cribari-Neto, Improved maximum
likelihood estimation in a new class of beta regression models,
Brazilian Journal of Probability and Statistics 19 (2005), 13-31.
