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New Approaches to Statistical Learning of Modern Time Series Chain Coordination
New Approaches to Statistical Learning of Modern Time Series Chain Coordination
New Approaches to Statistical Learning of Modern Time Series Chain Coordination
New Approaches to Statistical Learning of Modern Time Series Chain Coordination
20Mar
Seminar Calendar, Information and Innovation Management

New Approaches to Statistical Learning of Modern Time Series Chain Coordination

20 March 2023 | 2:30 p.m. — 4:00 p.m.
KK1121
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SPEAKER

Professor Rong Chen
Distinguished Professor of Statistics
Chair, Department of Statistics
Rutgers University

ABSTRACT

The BIGDATA era, many new forms of data have become available and useful in various important applications. When these data are observed over time, they form new types of time series that require new statistical models and analytical tools in order to extract useful information. In this talk we present new developments in analyzing matrix/tensor time series, dynamic networks, functional time series and compositional time series, with applications ranging from economics, finance, international trade, electricity loading and others. We will also briefly discuss approaches on modeling other forms of time series, including text time series and dynamic social networks.

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Professor Linbo Wang
New Approaches to Statistical Learning of Modern Time Series Chain Coordination
About Speaker
Prof. Rong Chen

Distinguished Professor | Department of Statistics and Biostatistics | Rutgers University

New Approaches to Statistical Learning of Modern Time Series Chain Coordination
20 March 20232:30 p.m. — 4:00 p.m.
KK1121
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