Voir la notice de l'article provenant de la source Library of Science
@article{DMPS_2016_36_1-2_a0, author = {Stawiarski, Bartosz}, title = {On non-existence of moment estimators of the {GED} power parameter}, journal = {Discussiones Mathematicae. Probability and Statistics}, pages = {5--23}, publisher = {mathdoc}, volume = {36}, number = {1-2}, year = {2016}, language = {en}, url = {http://geodesic.mathdoc.fr/item/DMPS_2016_36_1-2_a0/} }
TY - JOUR AU - Stawiarski, Bartosz TI - On non-existence of moment estimators of the GED power parameter JO - Discussiones Mathematicae. Probability and Statistics PY - 2016 SP - 5 EP - 23 VL - 36 IS - 1-2 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/DMPS_2016_36_1-2_a0/ LA - en ID - DMPS_2016_36_1-2_a0 ER -
Stawiarski, Bartosz. On non-existence of moment estimators of the GED power parameter. Discussiones Mathematicae. Probability and Statistics, Tome 36 (2016) no. 1-2, pp. 5-23. http://geodesic.mathdoc.fr/item/DMPS_2016_36_1-2_a0/
[1] A. Ayebo and T.J. Kozubowski, An asymmetric generalization of Gaussian and laplace laws, J. Probab. Statist. Sci. 1 (2) (2004), 187-210.
[2] A. Azzalini, Further results on a class of distributions which includes the normal ones, Statistica 46 (1986), 199-208.
[3] P.J. Bickel and D.A. Freedman, Some asymptotic theory for the bootstrap, Ann. Stat. 9 (6) (1981), 1196-1217.
[4] G.E. Box and G.C. Tiao, Bayesian Inference in Statistical Analysis (Addison Wesley Ed., 1973).
[5] Y. Chen and N.C. Beaulieu, Novel low-complexity estimators for the shape parameter of the Generalized Gaussian Distribution, IEEE Transactions on Vehicular Technology 58 (4) (2009), 2067-2071.
[6] D. Coin, A method to estimate power parameter in exponential power distribution via polynomial regression, Banca D’Italia 834 (2011), working paper.
[7] C. Fernandez, J. Osiewalski and M.F.J. Steel, Modeling and inference with vdistributions, J. Amer. Statist. Association 90 (432) (1995), 1331-1340.
[8] G. González-Farías, J.A. Domnguez-Molina and R.M. Rodrguez-Dagnino, Efficiency of the approximated shape parameter estimator in the generalized Gaussian distribution, IEEE Transactions on Vehicular Technology 58 (8) (2009), 4214-4223.
[9] R. Krupiński and J. Purczyński, Approximated fast estimator for the shape parameter of Generalized Gaussian Distribution, Signal Processing 86 (2006), 205-211.
[10] G. Lunetta, Di una generalizzazione dello schema della curva normale, Annali della Facolta di Economia e Commercio di Palermo 17 (1963), 237-244.
[11] S. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Trans. Pattern Anal. Machine Intell. 11 (1989), 674-693.
[12] A.M. Mineo and M. Ruggieri, A software tool for the exponential power distribution: The normalp package, J. Statist. Software 12 (4) (2005), 1-24.
[13] S. Nadarajah, A generalized normal distribution, J. Appl. Stat. 32 (7) (2005), 685-694.
[14] J. Purczyński, Simplified method of GED distribution parameters estimation, Folia Oeconomica Stetinensia 10 (2) (2012), 35-49.
[15] K.-S. Song, A globally convergent and consistent method for estimating the shape parameter of a Generalized Gaussian Distribution, IEEE Transactions on Information Theory 52 (2) (2006), 510-527.
[16] M.T. Subbotin, On the law of frequency of errors, Matematicheskii Sbornik 31 (1923), 296-301.
[17] P.R. Tadikamalla, Random sampling from the exponential power distribution, J. Amer. Statist. Association 75 (1980), 683-686.
[18] Van der Vaart, Asymptotic Statistics (Cambridge University Press, 1998).
[19] M.K. Varanasi and B. Aazhang, Parametric generalized Gaussian density estimation, J. Acoustical Society of America 86 (4) (1989), 1404-1415.
[20] D. Zhu and V. Zinde-Walsh, Properties and estimation of asymmetric exponential power distribution, J. Econometrics 148 (2009), 86-99.