Skip to content

IAI Actuarial Core Principles · Risk Modelling and Survival Analysis · Maximum likelihood estimators for transition intensities

In a model with states Active, Withdrawn and Dead, a life who is observed Active for 3 years and then withdraws contributes what to the likelihood under constant intensities mu_AW and mu_AD?

The contribution is exp(-3(mu_AW + mu_AD)) times mu_AW: survival in the Active state for three years against both exits, then the density of the observed withdrawal.

  1. Aexp(-3(mu_AW + mu_AD)) mu_AWCorrect
  2. Bexp(-3 mu_AW) mu_AW
  3. Cexp(-3(mu_AW + mu_AD)) mu_AD
  4. Dexp(-3 mu_AD) mu_AW
  5. 3 mu_AW mu_AD

Explanation

The life stays in Active for 3 years with probability exp(-3(mu_AW+mu_AD)), then moves to Withdrawn with intensity mu_AW. Leaving out mu_AD from the exponent ignores that death was also a possible exit during the stay.

Did you get it right without looking?

One question tells you little. A timed set on Maximum likelihood estimators for transition intensities shows your real accuracy, how long you take and where you lose marks.

More Maximum likelihood estimators for transition intensities questions