The random weighting estimation and its convergence of population parameter for two poisson distribution

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 distrib...

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Bibliographic Details
Published in2008 10th International Conference on Control, Automation, Robotics and Vision pp. 1869 - 1871
Main Authors Yu-Ren Li, She-Sheng Gao, Pan Hu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2008
Subjects
Automatic control
Computer vision
Convergence
Parameter estimation
Poisson distribution
Probability
Random Weighting Estimation
Robot control
Robot vision systems
Robotics and automation
Statistical distributions
Testing
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Summary: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.
ISBN:9781424422869
1424422868
DOI:10.1109/ICARCV.2008.4795812