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Angus Macdonald

Emeritus Professor in the School of Mathematical and Computer Sciences at Heriot-Watt University

Articles written by Angus Macdonald

Stopping the clock on the Poisson process

"The true nature of the Poisson distribution will become apparent only in connection with the theory of stochastic processes\(\ldots\)"

Feller (1950)

Tags: Filter information matrix by tag: Poisson distribution, Filter information matrix by tag: survival models

The Curse of Cause of Death Models

Stephen's earlier blog explained the origin of the very useful result relating the life-table survival probability \({}_tp_x\) and the hazard rate \(\mu_{x+t}\), namely:

\[ {}_tp_x = \exp \left( - \int_0^t \mu_{x+s} \, ds \right). \qquad (1) \]

To complete the picture, we add the assumption that the future lifetime of a person now aged \(x\) is a random variable, denoted by \(T_x\), and the connection with expression (1) which is:

Tags: Filter information matrix by tag: cause of death, Filter information matrix by tag: competing risks

Introducing the Product Integral

Of all the actuary's standard formulae derived from the life table, none is more important in survival modelling than:

\[{}_tp_x = \exp\left(-\int_0^t\mu_{s+s}ds\right).\qquad(1)\]

Tags: Filter information matrix by tag: survival models, Filter information matrix by tag: survival probability, Filter information matrix by tag: force of mortality, Filter information matrix by tag: product integral

Everything points to Poisson

One recurring theme in our forthcoming book, Modelling Mortality with Actuarial Applications, is the all-pervading role of likelihoods that suggest the lurking presence of a Poisson distribution. A popular assumption in modelling hazard rates is that the number of deaths observed at any given age is a Poisson random variable, so perhaps that might explain it?

Tags: Filter information matrix by tag: survival data, Filter information matrix by tag: Poisson distribution