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A parameter estimation method for structural equation model based on generalized maximum entropy

机译:基于广义最大熵的结构方程模型参数估计方法

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摘要

In order to resolve the problem of parameter estimation in structural equation model, we introduce the entropy theory into parameter estimation. According to the principles of Generalized Maximum Entropy (GME), we study the results and performances of GME method and Partial Least Squares (PLS) method in solving parameters estimation of structural equation model in small-sized sample data. By comparison of two methods, we could conclude that GME method outperforms PLS method when dealing with small-sized sample data in stability and results. Finally, on the basis of this result, we provide some suggestions on solving parameter estimation of structural equation model in small-sized sample data.
机译:为了解决结构方程模型中参数估计的问题,我们将熵理论引入到参数估计中。根据广义最大熵(GME)的原理,我们研究了GME方法和偏最小二乘(PLS)方法在求解小样本数据中结构方程模型参数估计中的结果和性能。通过两种方法的比较,我们可以得出结论,在处理小样本数据的稳定性和结果上,GME方法优于PLS方法。最后,基于此结果,我们为解决小样本数据中结构方程模型的参数估计提供了一些建议。

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