# Generate data from a segmented model and plot it
  a = 2
  b = 0.125
  d = 2
  c = a*d^(3/2) - b*d
  x = c(0:50)/10
  set.seed(12345)
  y = (x<d)*a*x^(3/2) + (x>=d)*(b*x+c) + rnorm(51,0,0.5)

# Function to calculate sum of squared distance from observed value
  ss = function(parameters, y) {
    a = parameters[1]
    b = parameters[2]
    d = parameters[3]
    c = a*d^(3/2) - b*d
    sum((y - ((x<d)*a*x^(3/2) + (x>=d)*(b*x + a*d^(3/2) - b*d)))^2)
  }

sol = optim(c(1.5,0.1,1.5), ss, y=y)
sol$par
#[1] 2.05963514 0.04598089 2.01290367