Name
Abstract | ||
|---|---|---|
•Disease count time-series prediction is difficult due to unexpected trend change.•Analytics literature suggests a method that targets smooth changes.•Disease count may encounter abrupt trend changes.•The current paper addresses the abrupt changes in disease count data.•The method has been evaluated through disease count data in Nevada. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.ipm.2018.11.004 | Information Processing & Management |
Keywords | Field | DocType |
Time-series analysis,Structural trend change,Disease counts | Information system,Data mining,Time series,Disease,Computer science,Statistics,Analytics,Estimator | Journal |
Volume | Issue | ISSN |
56 | 3 | 0306-4573 |
Citations | PageRank | References |
1 | 0.35 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amir Talaei-Khoei | 1 | 52 | 15.63 |
| James M. Wilson | 2 | 3 | 1.09 |