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Original Articles

Shrinkage and pretest estimators for longitudinal data analysis under partially linear models

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Pages 531-549 | Received 11 Jun 2014, Accepted 12 Mar 2016, Published online: 06 Jun 2016

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Mai Ghannam & Sévérien Nkurunziza. (2022) The risk of tensor Stein-rules in elliptically contoured distributions. Statistics 56:2, pages 421-454.
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Hadi Emami. (2020) Improved estimation in elliptical linear mixed measurement error models. Journal of Statistical Computation and Simulation 90:9, pages 1681-1704.
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Le An Lac & Shakhawat Hossain. (2018) Non-penalty shrinkage estimation of random effect models for longitudinal data with AR(1) errors. Journal of Statistical Computation and Simulation 88:16, pages 3230-3247.
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Articles from other publishers (6)

Shakhawat Hossain, Saumen Mandal & Le An Lac. (2022) Pretest and shrinkage estimators in generalized partially linear models with application to real data. Canadian Journal of Statistics 51:4, pages 975-1003.
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Mai Ghannam & Sévérien Nkurunziza. (2022) Improved estimation in tensor regression with multiple change-points. Electronic Journal of Statistics 16:2.
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Shakhawat Hossain & Le An Lac. (2021) Optimal shrinkage estimations in partially linear single-index models for binary longitudinal data. TEST 30:4, pages 811-835.
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Shakhawat Hossain, Ian Hiebert & Saumen Mandal. (2019) Estimation strategy of multilevel model for ordinal longitudinal data. Japanese Journal of Statistics and Data Science 2:2, pages 299-322.
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Shakhawat Hossain, Trevor Thomson & Ejaz Ahmed. (2018) Shrinkage estimation in linear mixed models for longitudinal data. Metrika 81:5, pages 569-586.
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Xiaoli Gao, S. Ejaz Ahmed & Yang Feng. (2017) Rejoinder to ‘Post‐selection shrinkage estimation for high‐dimensional data analysis’. Applied Stochastic Models in Business and Industry 33:2, pages 131-135.
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