STATISTICAL ANALYSIS OF RED MEAT, WHITE MEAT AND EGG PRODUCTION AND CONSUMPTION IN NORTHERN IRAQ GOVERNMENT
| dc.contributor.advisor | Mikail, Nazire | |
| dc.contributor.author | Hasan, Hayman Murad | |
| dc.date.accessioned | 2019-11-28T17:42:17Z | |
| dc.date.available | 2019-11-28T17:42:17Z | |
| dc.date.issued | 2018 | en_US |
| dc.date.submitted | 2017-09 | |
| dc.department | Enstitüler, Fen Bilimleri Enstitüsü, Zootekni Ana Bilim Dalı | en_US |
| dc.description.abstract | The present study was undertaken to find out appropriate deterministic type forecasting model that could best describe the growth pattern of red meat, white meat and egg production and consumption in the Northern Iraq during the time periods 2009 to 2015. The study revealed using Akaike Information Criteria, that the ARIMA (0,1,1) model is the best fitted model for red meat, linear model is the best for chicken meat and exponential models best for fish meat and egg production, whereas quadratic models best fitted for red, chicken, fish meat and egg consumptions. The selected models were used for succeeding five years forecast with a 95% confidence interval of red meat, white meat and egg production and consumption. The findings of this study will help the policy makers to take necessary actions for proper management of red meat, white meat and egg production according to their demand and supply. | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12604/2028 | |
| dc.identifier.yoktezid | 476108 | |
| dc.institutionauthor | Mikail, Nazire | |
| dc.language.iso | en | en_US |
| dc.publisher | Siirt Üniversitesi, Fen Bilimleri Enstitüsü | en_US |
| dc.relation.publicationcategory | Tez | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.snmz | #KayıtKontrol# | |
| dc.subject | Red meat, white meat, egg, production, consumption, forecasting, time series analysis | en_US |
| dc.title | STATISTICAL ANALYSIS OF RED MEAT, WHITE MEAT AND EGG PRODUCTION AND CONSUMPTION IN NORTHERN IRAQ GOVERNMENT | en_US |
| dc.type | Master Thesis | en_US |
