Analysis of data including missing values in the Taguchi’s T method
2018 年 4 巻 2 号 p. 53-64
詳細
2018 年 4 巻 2 号 p. 53-64
The T (Taguchi) method is belongs to the MT (Mahalanobis Taguchi) system which is a representative method in quality engineering. The T method is used for prediction or estimation in fields such as economics and weather forecast.
Actual analyses often entail the presence of missing value, which make processing a model more complex. Overall, it is necessary to impute missing values with some other ones.
As highlighted by Masuda (2012), “Although not well-known, the T method has the merit that it is not in conventional multiple regression analysis. That is, even if missing data exists, it can be analyzed in the T method.” More specifically, the T method integrates the results of the single regression analysis, thus making it possible to perform analyses without processing missing values, if present. Then, based on this, the missing data analysis in the T method is taken into account.
In this study, we consider the development of the analysis of data including missing values. Specifically, we clarify the calculation procedure in the T method and its improvement with missing data, run simulations under various models, and compare the estimation accuracies.
