{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T00:56:16Z","timestamp":1779238576255,"version":"3.51.4"},"reference-count":25,"publisher":"MIT Press - Journals","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Computation"],"published-print":{"date-parts":[[2013,6]]},"abstract":"<jats:p> LiNGAM has been successfully applied to some real-world causal discovery problems. Nevertheless, causal sufficiency is assumed; that is, there is no latent confounder of the observations, which may be unrealistic for real-world problems. Taking into the consideration latent confounders will improve the reliability and accuracy of estimations of the real causal structures. In this letter, we investigate a model called linear nongaussian acyclic models in the presence of latent gaussian confounders (LiNGAM-GC) which can be seen as a specific case of lvLiNGAM. This model includes the latent confounders, which are assumed to be independent gaussian distributed and statistically independent of the disturbances. To tackle the causal discovery problem of this model, first we propose a pairwise cumulant-based measure of causal directions for cause-effect pairs. We prove that in spite of the presence of latent gaussian confounders, the causal direction of the observed cause-effect pair can be identified under the mild condition that the disturbances are simultaneously supergaussian or subgaussian. We propose a simple and efficient method to detect the violation of this condition. We extend our work to multivariate causal network discovery problems. Specifically we propose algorithms to estimate the causal network structure, including causal ordering and causal strengths, using an iterative root finding-removing scheme based on pairwise measure. To address the redundant edge problem due to the finite sample size effect, we develop an efficient bootstrapping-based pruning algorithm. Experiments on synthetic data and real-world data have been conducted to show the applicability of our model and the effectiveness of our proposed algorithms. <\/jats:p>","DOI":"10.1162\/neco_a_00444","type":"journal-article","created":{"date-parts":[[2013,3,21]],"date-time":"2013-03-21T15:56:17Z","timestamp":1363881377000},"page":"1605-1641","source":"Crossref","is-referenced-by-count":17,"title":["Causality in Linear Nongaussian Acyclic Models in the Presence of Latent Gaussian Confounders"],"prefix":"10.1162","volume":"25","author":[{"given":"Zhitang","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Chinese University of Hong Kong Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laiwan","family":"Chan","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Chinese University of Hong Kong Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1162\/089976699300016458"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44491-2_78"},{"key":"B3","first-page":"2515","volume-title":"Proceedings of the 2002 International Joint Conference on Neural Networks","volume":"3","author":"Chan L.","year":"2002"},{"key":"B4","volume-title":"Proceedings of 3rd International Conference on Independent Component Analysis and Blind Signal Separation","author":"Chan L.","year":"2001"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-28551-6_3"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1016\/0165-1684(94)90029-9"},{"key":"B7","first-page":"143","volume-title":"Proceedings of the Proceedings of the Twenty-Sixth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-10)","author":"Daniu\u0161is P.","year":"2010"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-25655-4_17"},{"key":"B9","first-page":"863","volume":"12","author":"Henao R.","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2008.02.006"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1109\/97.763148"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(00)00026-5"},{"key":"B13","first-page":"111","volume":"14","author":"Hyv\u00e4rinen A.","year":"2013","journal-title":"Journal of Machine Learning Research"},{"key":"B14","first-page":"249","volume-title":"Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence","author":"Janzing D.","year":"2009"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.02.008"},{"key":"B17","first-page":"031","volume":"2010","author":"Moneta A.","year":"2010","journal-title":"Jena Economic Research Papers"},{"key":"B18","volume-title":"Causality: Models, reasoning, and inference","author":"Pearl J.","year":"2000"},{"key":"B19","first-page":"2003","volume":"7","author":"Shimizu S.","year":"2006","journal-title":"Journal of Machine Learning Research"},{"key":"B20","first-page":"1225","volume":"12","author":"Shimizu S.","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2011.05.017"},{"key":"B22","volume-title":"Causation, prediction, and search","author":"Spirtes P.","year":"2000"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2003.10.014"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1007\/11893295_45"},{"key":"B25","first-page":"2455","volume":"9","author":"Zhang K.","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1080\/14697680802039840"}],"container-title":["Neural Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/NECO_a_00444","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:39:51Z","timestamp":1615585191000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/neco\/article\/25\/6\/1605-1641\/7889"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,6]]},"references-count":25,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2013,6]]}},"alternative-id":["10.1162\/NECO_a_00444"],"URL":"https:\/\/doi.org\/10.1162\/neco_a_00444","relation":{},"ISSN":["0899-7667","1530-888X"],"issn-type":[{"value":"0899-7667","type":"print"},{"value":"1530-888X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,6]]}}}