<http://webisa.webdatacommons.org/389920930>	<http://www.w3.org/ns/prov#wasQuotedFrom>	<upenn.edu> .
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<http://webisa.webdatacommons.org/389920930>	<http://www.w3.org/ns/prov#value>	"Hau-Tieng Wu, Stanford University; Adaptive modeling of dynamic periodicity and trend with heteroscedastic and dependent errors -- with clinical applications\" 01/13/2014 - 10:00am - 11:00am Location: Chemistry Building, Lynch Lecture Hall Periodicity and trend are features describing an observed sequence, and extracting these features is an important issue in many scientific fields." .
<http://webisa.webdatacommons.org/prov/34452782>	<http://www.w3.org/ns/prov#wasDerivedFrom>	<http://webisa.webdatacommons.org/389920930> .