Valid properties of truncated Student-t regression model with applications in analysis of censored data-Reference-Cited by-同舟云学术

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Valid properties of truncated Student-t regression model with applications in analysis of censored data

Published:2022-03-01 Issue:1 Volume:36 Page:
ISSN:0103-0752
Container-title:Brazilian Journal of Probability and Statistics
language:
Short-container-title:Braz. J. Probab. Stat.

Author:

Zhang Chi¹,Tian Guo-Liang²,Zhai Yibo²,Fei Yu³

Affiliation:

1. College of Economics, Shenzhen University, Shenzhen 518055, Guangdong Province, P.R. China

2. Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen 518055, Guangdong Province, P.R. China

3. School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming 650221, Yunnan Province, P.R. China

Publisher

Institute of Mathematical Statistics

Subject

Statistics and Probability

Reference29 articles.

1. Arismendi, J. C. (2013). Multivariate truncated moments. Journal of Multivariate Analysis 117, 41–75.

2. Becker, M. P., Yang, I. and Lange, K. (1997). EM algorithms without missing data. Statistical Methods in Medical Research 6, 38–54.

3. Cohen, A. C. Jr. (1949). On estimating the mean and standard deviation of truncated normal distributions. Journal of the American Statistical Association 44, 518–525.

4. Cohen, A. C. Jr. (1950). Estimating the mean and variance of normal populations from singly truncated and doubly truncated samples. The Annals of Mathematical Statistics 21, 557–569.

5. Cohen, A. C. Jr. (1959). Simplified estimators for the normal distribution when samples are singly censored or truncated. Technometrics 1, 217–237.

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