Bibliography

Aitkin, Murray. 2010. Statistical Inference. An Integrated Bayesian Likelihood Approach. Boca Raton, FL: Chapman & Hall/CRC.

Akaike, H. 1978. “Covariance Matrix Computations of the State Variable of a Stationary Gaussian Process.” Annals of the Institute of Statistical Mathematics 30 (B): 499–504.

Baddeley, Adrian, and Rolf Turner. 2005. “Spatstat: An R Package for Analyzing Spatial Point Patterns.” Journal of Statistical Software 12 (6): 1–42. www.jstatsoft.org.

Carvalho, Marilia Sá, Valeska Lima Andreozzi, Claudia Torres Codeço, Dayse Pereira Campos, Maria Tereza Serrano Barbosa, and Silvia Emiko Shimakura. 2011. Análise de Sobrevivência: Teoria e Aplicações Em Saúde. 2nd ed. Editora Fiocruz.

Clélia M. C. Toloi, Pedro Alberto Morettin &. 2004. Analise de Series Temporais. Projeto Fisher. Associação Brasileira de Estatística e Edgard Blücher.

De Jong, P. 1988. “The Likelihood for a State Space Model.” Biometrika 75 (1): 165–69.

Diggle, P. J., and P. J. Ribeiro Jr. 2007. Model Based Geostatistics. New York: Springer.

Diggle, Peter J. 2003. Statistical Analysis of Spatial Point Patterns. 2nd ed. Hodder Education Publishers.

Gardner, G, A. C. Harvey, and G. D. A. Phillips. 1980. “An Algorithm for Exact Maximum Likelihood Estimation by Means of Kalman Filtering.” Applied Statistics 29 (3): 311–22.

Giolo, S R, and E A Colosimo. 2006. Análise de Sobreviência Aplicada. Edgard Blucher.

Harvey, A. C. 1981. Time Series Models. Wiley.

Harvey, A. C., and G. D. A. Phillips. 1979. “Maximum Likelihood Estimation of Regression Models with Autoregressive-Moving Average Disturbances.” Biometrika 66 (1): 49–58.

Jones, R. H. 1980. “Maximum Likelihood Fitting of ARMA Models to Time Series with Missing Observations.” Technometrics 22 (3): 389–95.

Kalman, R. E. 1960. “A New Approach to Linear Filtering and Prediction Problems.” Journal of Basic Engineering 82 (1): 35–45.

Miyashiro, Eliane Shizue. 2008. “Modelos de Regressão Beta e Simplex Para a análise de Proporções.” São Paulo: Universidade de São Paulo.

Nelder, J. A., and R. M. Wedderburn. 1972. “Generalized Linear Models.” Journal of the Royal Statistical Society, Series A 135: 370–84.

Pawitan, Yudi. 2001. In All Likelihood: Statistical Modelling and Inference Using Likelihood. Oxford University Press, USA. http://www.amazon.com/All-Likelihood-Statistical-Modelling-Inference/dp/0198507658.

Petris, Giovanni, Sonia Petrone, and Patrizia Campagnoli. 2009. Dynamic Linear Models with r. Springer-Verlag, New York.

Rizzo, Maria L. 2008. Statistical Computing with R. Boca Raton, FL: Chapman & Hall/CRC.

Royall, R. 1997. Statistical Evidence. Chapman; Hall.

Schweppe, F. C. 1965. “Evaluation of Likelihood Functions for Gaussian Signals.” IEEE Trans. Info. Theory 11: 61–70.

Soetaert, Karline. 2009. rootSolve: Nonlinear Root Finding, Equilibrium and Steady-State Analysis of Ordinary Differential Equations.

West, M., and J. Harrison, eds. 1997. Bayesian Forecasting and Dynamic Models. 2nd ed. New York: Springer-Verlag.

Winkelmann, Rainer. 1995. “Duration Dependence and Dispersion in Count-Data Models.” Journal of Business & Economic Statistics 13 (4): 467–74. https://doi.org/10.2307/1392392.