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Nowadays, the parameter setting of the Spring Festival model mainly depends on subjective judgement for researchers. To solve the problem, firstly, the paper introduces factor-adjusted general process on Spring Festival and relevant details for model specification and model inspection. On this basis, the paper puts forward new ideas on selecting automatically Spring Festival model with optimal parameters based on "loop through" and sequential test method. Taking Spring Festival model's optimal effective phase length recognition of total retail sales of social consumer goods as an example, we examine its feasibility and validity. The empirical results show that the sequential test method based on seasonal peaks, outliers, Q statistics, AICC values, and BIC values can effectively identify the optimal infulence period length of the Spring Festival model, which can efficiently improve seasonal adjustment performance on Spring Festival model. [ABSTRACT FROM AUTHOR]