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Volume 12, Issue 2
Testing for outliers in nonlinear longitudinal data models based on M-estimation

Huihui Sun

J. Info. Comput. Sci. , 12 (2017), pp. 107-112.

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  • Abstract
In this paper we propose and analyze nonlinear mixed-effects models for longitudinal data, obtaining robust maximum likelihood estimates for the parameters by introducing Huber’s function in the log-likelihood function. Furthermore, the test for outliers in the model based on robust estimation is investigated through generalized Cook’s distance. The obtained results are illustrated by plasma concentrations data presented in Davidian and Giltiman, which was analyzed under the non-robust situation.
  • Keywords

M-estimation nonlinear mixed models longitudinal data testing for outliers generalized Cook’s distance.

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COPYRIGHT: © Global Science Press

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@Article{JICS-12-107, author = {Huihui Sun}, title = {Testing for outliers in nonlinear longitudinal data models based on M-estimation}, journal = {Journal of Information and Computing Science}, year = {2017}, volume = {12}, number = {2}, pages = {107--112}, abstract = { In this paper we propose and analyze nonlinear mixed-effects models for longitudinal data, obtaining robust maximum likelihood estimates for the parameters by introducing Huber’s function in the log-likelihood function. Furthermore, the test for outliers in the model based on robust estimation is investigated through generalized Cook’s distance. The obtained results are illustrated by plasma concentrations data presented in Davidian and Giltiman, which was analyzed under the non-robust situation. }, issn = {3080-180X}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22486.html} }
TY - JOUR T1 - Testing for outliers in nonlinear longitudinal data models based on M-estimation AU - Huihui Sun JO - Journal of Information and Computing Science VL - 2 SP - 107 EP - 112 PY - 2017 DA - 2017/06 SN - 12 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22486.html KW - M-estimation KW - nonlinear mixed models KW - longitudinal data KW - testing for outliers KW - generalized Cook’s distance. AB - In this paper we propose and analyze nonlinear mixed-effects models for longitudinal data, obtaining robust maximum likelihood estimates for the parameters by introducing Huber’s function in the log-likelihood function. Furthermore, the test for outliers in the model based on robust estimation is investigated through generalized Cook’s distance. The obtained results are illustrated by plasma concentrations data presented in Davidian and Giltiman, which was analyzed under the non-robust situation.
Huihui Sun. (2017). Testing for outliers in nonlinear longitudinal data models based on M-estimation. Journal of Information and Computing Science. 12 (2). 107-112. doi:
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