References
- Azevedo, C., V. Leiva, E. Athayde, and N. Balakrishnan. 2012. Shape and change point analyses of the Birnbaum–Saunders-t hazard rate and associated estimation. Computational Statistics and Data Analysis 56:3887–97.
- Bouezmarni, T., and J. Rombouts. 2010. Nonparametric density estimation for multivariate bounded data. Journal of Statistical Planning and Inference 140:139–52.
- Chen, S. 1999. Beta kernels estimators for density functions. Computational Statistics and Data Analysis 31:131–45.
- Chen, S. 2000. Gamma kernel estimators for density functions. Annals of the Institute of Statistical Mathematics 52:471–80.
- Cowling, A., and P. Hall. 1996. On pseudodata methods for removing boundary effects in kernel density estimation. Journal of the Royal Statistical Society, Series B 58:551–63.
- Funke, B., and R. Kawka. 2015. Nonparametric density estimation for multivariate bounded data using two non-negative multiplicative bias correction methods. Computational Statistics and Data Analysis 92:148–62.
- Hagmann, M., and O. Scaillet. 2007. Local multiplicative bias correction for asymmetric kernel density estimators. Journal of Econometrics 141:213–49.
- Hirukawa, M. 2010. Nonparametric multiplicative bias correction for kernel-type density estimation on the unit interval. Computational Statistics and Data Analysis 54:473–95.
- Hirukawa, M., and M. Sakudo. 2014. Nonnegative bias reduction methods for density estimation using asymmetric kernels. Computational Statistics and Data Analysis 75:112–23.
- Hirukawa, M., and M. Sakudo. 2015. Family of the generalised gamma kernels: a generator of asymmetric kernels for nonnegative data. Journal of Nonparametric Statistics 27:41–63.
- Jin, X., and J. Kawczak. 2003. Birnbaum–Saunders and lognormal kernel estimators for modelling durations in high frequency financial data. Annals of Economics and Finance 4:103–24.
- Johnson, R., and D. Wichern. 1999. Applied multivariate analysis. 4th ed. New Jersey: Prentice-Hall.
- Jones, M., and P. Foster. 1996. A simple nonnegative boundary correction method for kernel density estimation. Statistica Sinica 6:1005–13.
- Jones, M., O. Linton, and J. Nielsen. 1995. A simple bias reduction method for density estimation. Biometrika 82:327–38.
- Kokonendji, C., and T. Senga Kiessé. 2011. Discrete associated kernels method and extensions. Statistical Methodology 8:497–516.
- Kundu, D., N. Balakrishnan, and A. Jamalizadeh. 2010. Bivariate Birnbaum–Saunders distribution and associated inference. Journal of Multivariate Analysis 101:113–25.
- Kundu, D., N. Balakrishnan, and A. Jamalizadeh. 2013. Generalized multivariate Birnbaum–Saunders distributions and related inferential issues. Journal of Multivariate Analysis 116:230–44.
- Leiva, V., F. Vilca, N. Balakrishnan, and A. Sanhueza. 2010. A skewed sinh-Normal distribution and its properties and application to air pollution. Communications in Statistics-Theory and Methods 39:426–43.
- Marchant, C., K. Bertin, V. Leiva, and H. Saulo. 2013. Generalized Birnbaum–Saunders kernel density estimators and an analysis of financial data. Computational Statistics and Data Analysis 63:1–15.
- Marchant, C., V. Leiva, and F. Cysneiros. 2016a. A multivariate log-linear model for Birnbaum–Saunders distributions. IEEE Transactions on Reliability 65:816–27.
- Marchant, C., V. Leiva, F. Cysneiros, and J. Vivanco. 2016b. Diagnostics in multivariate Birnbaum–Saunders regression models. Journal of Applied Statistics 43:2829–49.
- Müller, H. 1991. Smooth optimum kernel estimators near endpoints. Biometrika 78:521–30.
- Parzen, E. 1962. On estimation of a probability density function and mode. Annals of Mathematical Statistics 33:1065–76.
- R Development Core Team. 2016. A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna: Austria. http://www.R-project.org.
- Rosenblatt, M. 1956. Remarks in some nonparametric estimates of a density function. Annals of Mathematical Statistics 27:832–7.
- Saulo, H., V. Leiva, F. Ziegelmann, and C. Marchant. 2013. A nonparametric method for estimating asymmetric densities based on skewed Birnbaum–Saunders distributions applied to environmental data. Stochastic Environmental Research and Risk Assessment 7:1479–91.
- Scaillet, O. 2004. Density estimation using inverse and reciprocal inverse Gaussian kernels. Journal of Nonparametric Statistics 16:217–26.
- Schuster, E. 1985. Incorporating support constraints into nonparametric estimators of densities. Communications in Statistics-Theory and Methods 14:1123–36.
- Terrell, G., and D. Scott. 1980. On improving convergence rates for nonnegative kernel density estimators. Annals of Statistics 8:1160–63.
- Zougab, N., and S. Adjabi. 2016. Multiplicative bias correction for generalized Birnbaum-Saunders kernel density estimators and application to nonnegative heavy tailed data. Journal of the Korean Statistical Society 45:51–63.