Correlation analysis of mutual information by probability density estimated from improved averaged-shifted-histogram
改进型平均移位柱状图估算概率密度并对互信息作相关分析

We introduce the method of improved averaged-shifted-histogram(IASH) to estimate the probability density by combining the quadratic smooth weight with the uniform smooth weight. The ratio of the original smooth weight to the uniform smooth weight is dynamically adjusted according to the variance of the number of samples in the corresponding interval, thus the smooth weight for the edge part of the probability density obtained by the method of averaged-shiftedhistogram(ASH) is proportionally compensated, mitigating the excessive smoothness and improving the precision in the estimation of probability density by the method of IASH. Using the estimated probability density, we perform the correlation analysis based on the mutual information between two variables, and select input variables to predict the multivariate time series. Simulations with the synthetic data and Housing data show the efficacy of the proposed method.