| Title |
Modelling integer-valued autoregressive processes with application to covid-19 data / |
| Translation of Title |
Sveikareikšmių autoregresijos procesų modeliavimas ir taikymas COVID-19 duomenims. |
| Authors |
Dulkevičiūtė, Jūratė |
| Full Text |
|
| Pages |
48 |
| Keywords [eng] |
INAR, Seasonal INAR, Bivariate INAR, COVID-19, Poisson distribution, Negative Binomial distribution, General Poisson distribution. |
| Abstract [eng] |
This work introduces an integer-valued autoregressive model and its extensions: seasonal INAR, bivariate INAR. Three estimation methods: method of moments, conditional least squares and conditional maximum likelihood, are presented for models with Poisson, Negative Binomial and Generalized Poisson distributions. The described methods are tested on simulated data and applied on COVID-19 cases and deaths for Lithuania, Croatia, Estonia and Israel. Lastly, a short term forecast is presented. |
| Dissertation Institution |
Vilniaus universitetas. |
| Type |
Master thesis |
| Language |
English |
| Publication date |
2022 |
