MLGL: An R Package Implementing Correlated Variable Selection by Hierarchical Clustering and Group-Lasso by Quentin Grimonprez, Samuel Blanck, Alain Celisse, Guillemette Marot

Subjects: “…penalized regression…”
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Utilizing RNA-seq data in monotone iterative generalized linear model to elevate prior knowledge quality of the circRNA-miRNA-mRNA regulatory axis by Alikhan Anuarbekov, Jiří Kléma

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Development and Validation of Predictive Risk Scores for Ovarian Clear Cell Carcinoma: A Penalized Regression Model by Shohei Iyoshi, Ryo Emoto, Nobuhisa Yoshikawa, Kosuke Yoshida, Masato Yoshihara, Satoshi Tamauchi, Akira Yokoi, Yusuke Shimizu, Yoshiki Ikeda, Kaoru Niimi, Michiyasu Kawai, Shigeyuki Matsui, Hiroaki Kajiyama

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Estimating Optimal Treatment Rule for Major Depressive Disorder Using Penalized Regression Method by Narges Ghorbani, Ghodratollah Roshanaei, Vajihe Ramezani-Doroh, Alireza Soltanian, Mahya Arayeshgary, Leili Tapak

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Teachers’ team innovativeness in TALIS 2018: An empirical and simulation study using glmmLasso for multilevel data by Miryeong Koo, Jin Eun Yoo

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Evaluating Prediction Performance: A Simulation Study Comparing Penalized and Classical Variable Selection Methods in Low-Dimensional Data by Edwin Kipruto, Willi Sauerbrei

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