Forecasting counting and time statistics of compound Cox processes: a focus on intensity phase type process, deletions and simultaneous events-Reference-Cited by-同舟云学术

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Forecasting counting and time statistics of compound Cox processes: a focus on intensity phase type process, deletions and simultaneous events

Published:2019-02-07 Issue:1 Volume:62 Page:235-265
ISSN:0932-5026
Container-title:Statistical Papers
language:en
Short-container-title:Stat Papers

Author:

Bouzas Paula R.,Ruiz-Fuentes Nuria,Montes-Gijón Carmen,Ruiz-Castro Juan Eloy

Funder

Ministerio de Economía y Competitividad

Consejería de Innovación de la Junta de Andalucía

Consejer?a de Econom?a, Innovaci?n, Ciencia y Empleo, Junta de Andaluc?a

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://link.springer.com/article/10.1007/s00362-019-01092-0/fulltext.html

Reference32 articles.

1. Aguilera AM, Ocaña FA, Valderrama MJ (1997) An approximated principal component prediction model for continuous-time stochastic processes. Appl Stoch Models Data Anal 13:61–72

2. Asha G, Nair UN (2010) Reliability properties of mean time to failure in age replacement models. Int J Reliab Qual Saf Eng 17:15–26

3. Barta P, Miller M, Qiu A (2005) A stochastic model for studying the laminar structure of cortex from mri. IEEE Trans Med Imaging 24:728–742

4. Bieniek M, Goroncy A (2017) Sharp lower bounds on expectations of GOS based on DGFR distributions. Stat Pap. https://doi.org/10.1007/s00362-017-0972-y

5. Bouzas PR, Aguilera AM, Valderrama MJ (2002) Forecasting a class of doubly stochastic Poisson processes. Stat Pap 43:507–523

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