Title :
The random weighting estimation and its convergence of population parameter for two poisson distribution
Author :
Li, Yu-Ren ; Gao, She-Sheng ; Hu, Pan
Author_Institution :
Sch. of Automatics, Northwestern Polytech. Univ., Xi´´an
Abstract :
Random weighting estimation is a new method in statistics, which has many advantages such as good quality of large sample and simple computation. This method is applied to parameter estimation of Poisson distribution in this paper. Firstly, the population parameter estimation for two Poisson distribution with is studied. Secondly, the random weighting estimation is applied in population parameters of two Poisson distribution with partially missing data. Finally, the convergence of the random weighting estimation of population parameters of two Poisson distribution with partially missing data is proved rigorously under the certain condition. Research results show that the new method has a better performance than traditional estimation methods do.
Keywords :
Poisson distribution; parameter estimation; random processes; Poisson distribution; partially missing data; population parameter estimation; random weighting estimation; Automatic control; Computer vision; Convergence; Parameter estimation; Probability; Robot control; Robot vision systems; Robotics and automation; Statistical distributions; Testing; Convergence; Poisson distribution; Random Weighting Estimation;
Conference_Titel :
Control, Automation, Robotics and Vision, 2008. ICARCV 2008. 10th International Conference on
Conference_Location :
Hanoi
Print_ISBN :
978-1-4244-2286-9
Electronic_ISBN :
978-1-4244-2287-6
DOI :
10.1109/ICARCV.2008.4795812