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Teng-Zhong Rong

Publications (4)

A Recommendation for Classical and Robust Factor Analysis

Ying-Ying Zhang, Teng-Zhong Rong & Man-Man Li · Journal of Advances in Mathematics and Computer Science · 2017

Considering the factor analysis methods (classical or robust), the data input (data or scaled data), and the running matrix (covariance or correlation) all together, there are 8 combinations. The objective of the study is to give a recommendation for classical and robust factor a...

Open access Research Article 10.9734/BJMCS/2017/31936

The Behrens-Fisher Problem: A Z Distribution Approach

Ying-Ying Zhang, Teng-Zhong Rong & Man-Man Li · Journal of Advances in Mathematics and Computer Science · 2017

We propose the Z distribution to tackle the Behrens-Fisher problem. First, we define the Z distribution which is a generalization of the t distribution, and then nd the pdf and cdf of the Z distribution. After that, we apply the Z distribution in the hypothesis testing of two nor...

Open access Research Article 10.9734/BJMCS/2017/31815

Coverage Probability of the Credible Interval and Credible Probability of the Confidence Interval of the Hierarchical Normal Model

Ying-Ying Zhang & Teng-Zhong Rong · Journal of Advances in Mathematics and Computer Science · 2017

It is well known that the coverage probability of a given nominal level confidence interval and the credible probability of a given nominal level credible interval will attain the nominal level. Moreover, it is commonly believed that the two switching concepts probabilities, that...

Open access Research Article 10.9734/BJMCS/2017/31816

The Posterior Distributions, the Marginal Distributions and the Normal Bayes Estimators of Three Hierarchical Normal Models

Ying-Ying Zhang, Wen-He Song & Teng-Zhong Rong · Journal of Advances in Mathematics and Computer Science · 2017

We calculate the posterior distributions, the marginal distributions and the normal Bayes estimators of three hierarchical normal models in the same manner. The three models are displayed in increasing complexity. We find that the posterior distributions and the marginal distribu...

Open access Research Article 10.9734/BJMCS/2017/31814