#Global variables:
#G=gender (0 for men, 1 for women),
#R=risk (0 for dødsrisiko/mortality risk, 1 for opplevelsesrisiko/longevity)

w <- function(x){
  if(G==0){
    return( pmin(2.671548-0.17248*x+0.001485*x^2,0) )
  }
  if(G==1){
    return( pmin(1.287968-0.10109*x+0.000814*x^2,0) )
  }
}

my.kol.2013 <- function(x){
  #menn
  if(G==0){
    #dødsrisiko
    if(R==0){
      return( (0.241752+0.004536*10^(0.051*x))/1000 )
    }
    #opplevelsesrisiko
    if(R==1){
      return( (0.189948+0.003564*10^(0.051*x))/1000 )
    }
  }
  #kvinner
  if(G==1){
    #dødsrisiko
    if(R==0){
      return( (0.085411+0.003114*10^(0.051*x))/1000 )
    }
    #opplevelsesrisiko
    if(R==1){
      return( (0.067109+0.002446*10^(0.051*x))/1000 )
    }
  }
}

my.kol <- function(x,t){
  return(my.kol.2013(x)*(1+w(x)/100)^(t-2013))
}

#Example of plots for R=0 and both genders
R <- 0
x0 <- 35
t0 <- 2023
my.kol.val <- function(u) my.kol(x0+u,t0+u)

G <- 0
x.val <- seq(0,100,by=1)
y.val.m <- sapply(x.val,my.kol.val)
G <- 1
y.val.w <- sapply(x.val,my.kol.val)
plot(x.val,y.val.m, type="l", col="red")
lines(x.val,y.val.w, type="l", col="blue")