Abstract
The paper gives a new approach to statistical simulation and resampling by the use of number-theoretic methods and representative points. Resempling techniques take samples from an approximate population. The bootstrap suggests to use a random sample to form an approximate population. We propose to construct some approximate population distribution by the use of two kinds of representative points, and samples are taken from these approximate distributions. The statistical inference is based on those samples. The statistical inference in this paper involves estimation of mean, variance, skewness, kurtosis, quantile and density of the population distribution. Our results show that the new method can significantly improve the results by the use of Monte Carlo methods.
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Fang, K., Zhou, M. & Wang, W. Applications of the representative points in statistical simulations. Sci. China Math. 57, 2609–2620 (2014). https://doi.org/10.1007/s11425-014-4860-9
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DOI: https://doi.org/10.1007/s11425-014-4860-9
Keywords
- bootstrap
- kernel density estimation
- normal distribution
- representative points
- resampling
- statistical simulation