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Feb 22nd, 2019
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  1. years <- c(2005:2016)
  2.  
  3. count <- c(20535, 20526, 19694, 18452, 17402, 16551, 15679, 14691, 13409, 13378, 12772, 12417) #cases
  4.  
  5. pop<- c(68435380, 69295253, 70158111, 71051678, 72039206, 73142150, 74223628, 75175826, 76147624, 77181884, 78218478, 79277962) #population
  6.  
  7. glm(count~years+offset(log(pop)), family=poisson)
  8.  
  9. years <- c(2005:2016)
  10.  
  11. agecat <- c("0-4", "5-14", "15-24", "25-34", "35-44", "45-54", "55-64", "65+")
  12.  
  13. weight <- c(5, 11, 11.5, 12.5, 14, 14, 12.5, 19.5) #european standart population
  14.  
  15. countcat_2005 <- c(293, 942, 4962, 4461, 3201, 2831, 1886, 1959) #age-categorized count of the cases in 2005
  16.  
  17. popcat_2005 <- c(5979662, 12665031, 12679110, 11546527, 9426447, 7104654, 4432038, 4601908) #age-categorized population in 2005
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