The application discloses a kind of based on dynamic
confidence interval AB test test effect evaluation method, it is related to
big data analysis technical field, including, to historical
time series is carried out autoregression analysis, extraction autoregression coefficient, and according to
time series analysis theory obtains dynamic variance inflation factor, uses dynamic variance inflation factor to correct posterior distribution variance, generates corrected posterior distribution variance;By the mean of posterior distribution and corrected posterior distribution variance Double optimization dynamic
confidence interval is constructed, compares double optimization dynamic
confidence interval with preset
sequential test boundary and makes decision, generates evaluation decision;Based on evaluation decision, the mean of posterior distribution and corrected posterior distribution variance are used as recommended parameter, set the initialization parameter recommendation of next stage AB test test, and integration generates AB test test effect evaluation report.The application enhances the accuracy and robustness of confidence interval.