The name is absent

Step 4, => Keep updating β^im+1'> and ^^m+1^ until they converge respectively

Step 5, ≠> Let m = m + l, repeat steps 2, 3 and 4 until β(^m+1'> and β^^l+1^ⁱ converge
respectively.

Consequently, we could get estimated hazard functions Λ(∙) and Ψ(∙), and survival
functions S(∙) and R(β.

Specifically, at Step 1,

Assuming independent censoring, we fit two Cox proportional hazards models to
get initial estimators β^ and βc°'¹ for β and β_c, respectively. Then we use the Breslow
(1972) method to obtain estimators for baseline cumulative hazard functions, which
give estimates of baseline survival functions.

• Baseline survival functions

For an event T and i < k, we have

S^,o°∖θ = eτp{-A^(t)} = exp{-

obsi<t

For dependent censoring C and i < k, we have

• Marginal cumulative distribution functions

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