Weighted Edge Frequency Polygons Density Estimator

the frequency interpolation estimate derived from the The histogram, has been widely used In many different fields because of its simple calculation method. Research on the frequency interpolation estimated, Scholars have always been more concerned about this research topics, and published a number of the results of related works, It also been continuous development, in 1998, Jones[1]et al., in order to optimize the frequency interpolation estimate, proposed a edge frequency interpolation density estimation Where x ∈ [(2k - 1)bn/2, (2k+1)bn/2), bn represents the window width.Jones et al., In the case of independent samples meet gives Optimal window widths MISE about the corresponding edge frequency histogram density estimation.Edge frequency histogram density estimation on both sides of the frequency taken right treatment, etc. This article will use the unequally weighted method, by introducing a weighting coefficientλ, We proposed a new class of weighted edge frequency interpolation density estimationIn independent samples Sequences, This paper research related to the asymptotic nature of this new weighted edge frequency interpolation density estimation. First, study the variance item、bias and mean square error of the weighted edge frequency interpolation density estimation under con-ditions of independent samples. And on the basis of that, gives the selection method of optimal weight and optimal window width. Then, proved the uniformly strong consistency and asymptotic unbiasedness of the weighted edge frequency interpolation density estimation. At last, Select the normal distribution model, and use the thought of numerical simulation, The simulation results show the estimated effect of weighted edge frequency interpolation density estimation estimation good results. And select the 2017 test scores to further illustrate that the weighted edge frequency interpolation density estimation make a good results.