Fitting a sigmoind curve in R

sigmoid.R

# function needed for visualization purposes
sigmoid = function(params, x) {
  params[1] / (1 + exp(-params[2] * (x - params[3])))
}

x = 1:53
y = c(0,0,0,0,0,0,0,0,0,0,0,0,0,0.1,0.18,0.18,0.18,0.33,0.33,0.33,0.33,0.41,
  0.41,0.41,0.41,0.41,0.41,0.5,0.5,0.5,0.5,0.68,0.58,0.58,0.68,0.83,0.83,0.83,
  0.74,0.74,0.74,0.83,0.83,0.9,0.9,0.9,1,1,1,1,1,1,1)

# fitting code
fitmodel <- nls(y~a/(1 + exp(-b * (x-c))), start=list(a=1,b=.5,c=25))

# visualization code
# get the coefficients using the coef function
params=coef(fitmodel)

y2 <- sigmoid(params,x)
plot(y2,type="l")
points(y)