An Introduction to Multiple Time Series Analysis
Bibliographic Data
| ID | 9103314 |
|---|---|
| Authors | G C TlAO (University of Chicago, corresponding author) |
| Year | 1993 |
| Volume | 31 |
| Issue | supplement |
| Pages | YS71-YS74 |
| Publication date | 1993-05-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/00005650-199305001-00011 |
| OpenAlex | W3140458281 |
| Language | EN |
| Citations received | 4 |
An expository account of multiple time series analysis is presented. Modeling several related time series together makes it possible to ascertain dynamic leading, lagging, and feedback relationships among the series; to produce more efficient forecasts and, in some situations; to develop control schemes. Procedures for building linear vector autoregressive moving average models are sketched and illustrated. An extension to parallel vector time series in a hierarchical framework is given. (Med Care 1993; 31:YS71-YS74)
Biology · Machine learning · Series (stratigraphy) · Time series · Computer Science · Time Series Analysis and Forecasting
| Citations per year | 0.13 |
|---|---|
| Citation span | 1996 - 2025 (30) |
| Highly cited | No |