Motivated by the statistical inference problem in population genetics, we present a new sequential importance sampling with resampling strategy. The idea of resampling is key to the recent surge of popularity of sequential Monte Carlo methods in the statistics and engineering communities, but existing resampling techniques do not work well for coalescent-based inference problems in population g...

One can say about resampling methods by citation of Ph.Good from [17]: “The resampling methods – permutation, cross-validation, and the bootstrap – are easy to learn and easy to apply.” And further: “Introduced in the 1930s, the numerous, albeit straightforward, calculations resampling methods require were beyond the capabilities of primitive calculators then to use. ... Today, with a powerful ...

With the advent of digital age, data storage continues to grow rapidly, especially with development internet centers. The environmental impact this technological revolution has become a problem. As cost recordings decreases, amount unnecessary stored increases. This paper presents new algorithm for compressing series, which uses local measure relevance based on statistical characteristics. comp...