source("81.r")
# ucitavamo zbog funkcija Tn i rN_mesavina 

lambda_n_ocena_nova = function(x, B, a) {
  # x je matrica koja sadrzi 10 uzoraka (smestenih po redovima)
  # razlika u odnosu na prethodni zadatak: 
  # sada se uzorak razlikuje za svako i = 1:10
  lambda_n = rep(0, 10)
  Tn_b = matrix(0, 10, B)
  
  for(i in 1:10) {
    for(j in 1:B) {
      xb = sample(x[i, ], n, replace = T)
      Tn_b[i,j] = Tn(xb, x[i, ])
      if(Tn_b[i,j] <= a) {
        lambda_n[i] = lambda_n[i] + 1/B
      }
    }
  }
  return(lambda_n)
}

n = 50
B = 100
eps = c(0.1, 0.2)
tau = c(2, 3)

lambda_n_ocena_nova(replicate(10, rN_mesavina(n, c(0, 0), c(1, tau[1]), eps[1])), B, 0)
lambda_n_ocena_nova(replicate(10, rN_mesavina(n, c(0, 0), c(1, tau[2]), eps[1])), B, 0)
lambda_n_ocena_nova(replicate(10, rN_mesavina(n, c(0, 0), c(1, tau[1]), eps[2])), B, 0)
lambda_n_ocena_nova(replicate(10, rN_mesavina(n, c(0, 0), c(1, tau[2]), eps[2])), B, 0)