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Weighted Power Lomax Distribution and its Length Biased Version: Properties and Estimation Based on Censored Samples
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In this paper, a weighted version of the power Lomax distribution referred to the weighted power Lomax distribution, is introduced. The new distribution comprises the length biased and the area biased of the power Lomax distribution as new models as well as containing an existing model as the length biased Lomax distribution as special model. Essential distributional properties of the weighted power Lomax distribution are studied. Maximum likelihood and maximum product spacing methods are proposed for estimating the population parameters in cases of complete and Type-II censored samples. Asymptotic confidence intervals of the model parameters are obtained. A sample generation algorithm along with a Monte Carlo simulation study is provided to demonstrate the pattern of the estimates for different sample sizes. Finally, a real-life data set is analyzed as an illustration and its length biased distribution is compared with some other lifetime distributions.
Pakistan Journal of Statistics and Operation Research
Title: Weighted Power Lomax Distribution and its Length Biased Version: Properties and Estimation Based on Censored Samples
Description:
In this paper, a weighted version of the power Lomax distribution referred to the weighted power Lomax distribution, is introduced.
The new distribution comprises the length biased and the area biased of the power Lomax distribution as new models as well as containing an existing model as the length biased Lomax distribution as special model.
Essential distributional properties of the weighted power Lomax distribution are studied.
Maximum likelihood and maximum product spacing methods are proposed for estimating the population parameters in cases of complete and Type-II censored samples.
Asymptotic confidence intervals of the model parameters are obtained.
A sample generation algorithm along with a Monte Carlo simulation study is provided to demonstrate the pattern of the estimates for different sample sizes.
Finally, a real-life data set is analyzed as an illustration and its length biased distribution is compared with some other lifetime distributions.
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