Estimación del proceso de poisson no homogeneo
DOI:
https://doi.org/10.17533/udea.redin.26618Abstract
La estimación de la función de intensidad es un proceso de Poisson no-homogéneo es un problema complejo sobre el cual han surgido variados métodos de solución asociados con diversos estimadores. A pesar de haberse encontrado estimadores muy representativos, ha han sido lo suficiente para declarar el problema totalmente resuelto. Este trabajo se presentan varios métodos de estimación para la función de intensidad; son todos ellos extensiones de trabajo previos que originan nuevos estimadores para la literatura estadística. En la parte final, recurriendo a un ejemplo, se hacen comparaciones gráficas de las diferentes técnicas.Downloads
References
(1) E. Cinlar. lntroduction to Stochastic Processes. Prentice-Hall, inc. New Jersey. 1976.
(2) D. R. Cox and P. A. Lewis. The statistical analysis of series of eventos. Methuen, London. 1966.
(3) I. Dyner y L. Pérez. Tiempos en Poisson. Sometido a publicación. 1983.
(4) V. Epanechnikov. Nonparametric estimates of a multivariate probability density. Theory of Probability and its applications. 14, 153-58. 1969.
(5) J. Grandell, On stochastic processes generated by a stochastic intensiy function. Skand. Aktuar. Tidskrift. 54, 204-40. 1971.
(6) P. A. Lewis. Recent results in the statistical analysis of univariate point processes. Stochastic Point processes. Wiley, 1972.
(7) E. A. Nadaraya. On the integral mean square error of some non-parametric estimates for the density function. Theory of Probability and its applications. 133-41, 1974.
(8) E. Parzen. On estimation of a probability density function and mode. Annals of Math. Stat. 33, 1065-76. 1962.
(9) M. Rosenblatt. Remarks on some parametric estimates of a density function. Annals of Math. Stat. 27, 832-35, 1956.
(10) V. W. Steinijans. A stochastic point model for the ocurrence of major freezes in Lake Constance. Journal of the Royal Statistical Society (Series C) 25, 58-63. 1976.
(11) R. A. Tapia and J. R. Thompson. Non parametric probability density estimation. The johns Hopkns University Press. 1978.
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