Ming-Tien Tsai

collaborators

3 papers

math.ST2024

On the consistent estimators of the population covariance matrix and its reparameterizations

Ming-Tien Tsai, Chia-Hsian Tsai

For the high-dimensional covariance estimation problem, when $lim_{n \to \infty} p / n = c \in (0, 1)$ the orthogonally equivariant estimator of the population covariance matrix proposed…

math.ST2024

On the orthogonally equivariant estimators of a covariance matrix

Ming-Tien Tsai, Chia-Hsuan Tsai

In this note, when the dimension $p$ is large we look into the insight of the Mar $c ˇ$ enko-Pastur equation to get an explicit equality relationship, and use the obtained equa…

math.ST2024

The decomposite $T^{2}$ -test when the dimension is large

Chia-Hsuan Tsai, Ming-Tien Tsai

In this paper, we discuss tests for mean vector of high-dimensional data when the dimension $p$ is a function of sample size $n$ . One of the tests, called the decomposite $T^{2}$ -t…

On the consistent estimators of the population covariance matrix and its reparameterizations

On the orthogonally equivariant estimators of a covariance matrix

The decomposite T2-test when the dimension is large

The decomposite $T^{2}$ -test when the dimension is large