| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
Acknowledgment
|
|
|
|
16 |
1 |
p. 83
|
artikel
|
| 2 |
A hybrid of artificial neural network, exponential smoothing, and ARIMA models for COVID-19 time series forecasting
|
Safi, Samir K.
|
|
|
16 |
1 |
p. 25-35
|
artikel
|
| 3 |
A probabilistic epidemiological model
|
Switkay, Hal M.
|
|
|
16 |
1 |
p. 15-23
|
artikel
|
| 4 |
Comment on the paper “The science of statistics in victimhood culture: Dignity and dishonor”
|
Lipkovich, Ilya
|
|
|
16 |
1 |
p. 81-82
|
artikel
|
| 5 |
Inconsistencies in countries COVID-19 data revealed by Benford’s law
|
Moreau, Vitor Hugo
|
|
|
16 |
1 |
p. 73-79
|
artikel
|
| 6 |
Modeling COVID-19 positivity rates and hospitalizations in Texas
|
Kafle, Ram C.
|
|
|
16 |
1 |
p. 53-58
|
artikel
|
| 7 |
Social network analysis and community detection on spread of COVID-19
|
Wickramasinghe, Ashani Nuwanthika
|
|
|
16 |
1 |
p. 37-52
|
artikel
|
| 8 |
Spatial identification of component-based relative risks
|
Kadhem, Safaa K.
|
|
|
16 |
1 |
p. 65-72
|
artikel
|
| 9 |
Statistical methods for estimating cure fraction of COVID-19 patients in India
|
Sreedevi, E.P.
|
|
|
16 |
1 |
p. 59-64
|
artikel
|
| 10 |
Statistical modeling of pandemics and coronavirus
|
Mandel, Igor
|
|
|
16 |
1 |
p. 1-3
|
artikel
|
| 11 |
Using the Weibull distribution to model COVID-19 epidemic data
|
Moreau, Vitor Hugo
|
|
|
16 |
1 |
p. 5-14
|
artikel
|
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