| dc.creator |
Mwoya, Byaro |
|
| dc.creator |
Abel, Kinyondo |
|
| dc.date |
2018-09-03T09:24:29Z |
|
| dc.date |
2018-09-03T09:24:29Z |
|
| dc.date |
2018-09 |
|
| dc.date.accessioned |
2021-05-07T09:40:55Z |
|
| dc.date.available |
2021-05-07T09:40:55Z |
|
| dc.identifier |
http://hdl.handle.net/20.500.11810/4751 |
|
| dc.identifier |
https://doi.org/10.1016/j.ejim.2018.04.021 |
|
| dc.identifier.uri |
http://hdl.handle.net/20.500.11810/4751 |
|
| dc.description |
The correlation analysis in time series has received considerable attention. Its use plays an important role in the social sciences, finance and medical sciences. Spearman's or Pearson correlation coefficients are the most commonly used for estimation. The assumption such as stationarity makes the validity of time series correlation coefficients. |
|
| dc.language |
en |
|
| dc.publisher |
European Journal of Internal Medicine |
|
| dc.subject |
Time series data, Correlation, stationary and non-stationary data |
|
| dc.title |
No correlation between health care expenditure and mortality in the European Union |
|
| dc.type |
Journal Article, Peer Reviewed |
|