Generate exponential survival data with probability alpha of censorship

exponential_survival_data.py

def exponential_survival_data(n, cr=0.05, scale=1.):

    t = stats.expon.rvs(scale=scale, size=n)
    if cr == 0.0:
        return t, np.ones(n, dtype=bool)

    def pF(h):
        v = 1.0*h/scale
        return v / (np.exp(v)-1) - cr

    #find the threshold:
    h = newton(pF, 1., maxiter=500)

    #generate truncated data
    R = (1-exp(-h/scale))*stats.uniform.rvs(size=n)
    entrance = -log(1-R)*scale

    C = (t+entrance) < h #should occur 1-cr of the time.
    T = np.minimum(h-entrance,t)
    return T,C