Roberto Di Mari, Roberto Rocci, Stefano Antonio Gattone. Finite Mixture of Linear Regression Models: An Adaptive Constrained Approach to Maximum Likelihood Estimation. In Maria Brigida Ferraro, Paolo Giordani, Barbara Vantaggi, Marek Gagolewski, María Ángeles Gil, Przemyslaw Grzegorzewski, Olgierd Hryniewicz, editors, Soft Methods for Data Science, SMPS 2016, Rome, Italy, 12-14 September, 2016. Volume 456 of Advances in Intelligent Systems and Computing, pages 181-186, Springer, 2016. [doi]
@inproceedings{MariRG16,
title = {Finite Mixture of Linear Regression Models: An Adaptive Constrained Approach to Maximum Likelihood Estimation},
author = {Roberto Di Mari and Roberto Rocci and Stefano Antonio Gattone},
year = {2016},
doi = {10.1007/978-3-319-42972-4_23},
url = {https://doi.org/10.1007/978-3-319-42972-4_23},
researchr = {https://researchr.org/publication/MariRG16},
cites = {0},
citedby = {0},
pages = {181-186},
booktitle = {Soft Methods for Data Science, SMPS 2016, Rome, Italy, 12-14 September, 2016},
editor = {Maria Brigida Ferraro and Paolo Giordani and Barbara Vantaggi and Marek Gagolewski and María Ángeles Gil and Przemyslaw Grzegorzewski and Olgierd Hryniewicz},
volume = {456},
series = {Advances in Intelligent Systems and Computing},
publisher = {Springer},
isbn = {978-3-319-42971-7},
}