{"id":5870,"date":"2022-04-08T04:00:00","date_gmt":"2022-03-29T00:48:57","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&p=5870"},"modified":"2022-04-05T13:26:14","modified_gmt":"2022-04-05T04:26:14","slug":"2022-04-08-jc","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/2022-04-08-jc\/","title":{"rendered":"RTransferEntropy \u2014 Quantifying information flow between different time series using effective transfer entropy"},"content":{"rendered":"

We will discuss about “RTransferEntropy \u2014 Quantifying information flow between different time series using effective transfer entropy”, Behrendt et al<\/em>., SoftwareX<\/em>, 2019<\/p>\n

Abstract: This paper shows how to quantify and test for the information flow between two time series with Shannon transfer entropy and R\u00e9nyi transfer entropy using the\u00a0<\/span>R<\/span><\/span><\/span>\u00a0package\u00a0<\/span>RTransferEntropy<\/em>. We discuss the methodology, the bias correction applied to calculate effective transfer entropy and outline how to conduct statistical inference. Furthermore, we describe the package in detail and demonstrate its functionality by means of several simulated processes and present an application to financial time series.<\/span><\/p>\n

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We will discuss about “RTransferEntropy \u2014 Quantifying information flow between different time series using effective transfer entropy”, Behrendt et al., SoftwareX, 2019 Abstract: This paper shows how to quantify and … <\/p>\n

Continue reading “RTransferEntropy \u2014 Quantifying information flow between different time series using effective transfer entropy”<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"template":"","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[219],"class_list":["post-5870","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-journal-club","cat_journal-club"],"yoast_head":"\nRTransferEntropy \u2014 Quantifying information flow between different time series using effective transfer entropy - Biomedical Mathematics Group<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/2022-04-08-jc\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"RTransferEntropy \u2014 Quantifying information flow between different time series using effective transfer entropy - 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