# Information Matrix

## Filter Information matrix

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### Seasonal mortality and age

**Written by:**Stephen Richards

**Tags:**Filter information matrix by tag: season, Filter information matrix by tag: winter

### The Hermite model of mortality

In Richards (2012) I compared seventeen different parametric models for modelling the mortality of a portfolio of UK annuitants. The best-fitting model, i.e. the one with the lowest AIC, was the Makeham-Beard model:

\[\mu_x = \frac{e^\epsilon+e^{\alpha+\beta x}}{1+e^{\alpha+\rho+\beta x}}\qquad(1)\]

**Written by:**Stephen Richards

**Tags:**Filter information matrix by tag: Hermite splines, Filter information matrix by tag: extrapolation

### The Poisson assumption under the microscope

**Written by:**Iain Currie

### The cohort effects that never were

**Written by:**Alexandre Boumezoued

**Tags:**Filter information matrix by tag: cohort effect, Filter information matrix by tag: mortality improvements

### Mortality down under

**Written by:**Stephen Richards

**Tags:**Filter information matrix by tag: season, Filter information matrix by tag: winter, Filter information matrix by tag: cause of death

### Is your mortality model frail enough?

Mortality at post-retirement ages has three apparent stages:

**Written by:**Stephen Richards

**Tags:**Filter information matrix by tag: late-life mortality deceleration, Filter information matrix by tag: frailty, Filter information matrix by tag: heterogeneity

### Diabetes in the driving seat?

**Written by:**Gavin Ritchie

**Tags:**Filter information matrix by tag: longevity, Filter information matrix by tag: diabetes, Filter information matrix by tag: mortality improvements

### See You Later, Indicator

A recurring feature in my previous blogs, such as this one on information, is the *indicator* process:

\[Y^*(x)=\begin{cases}1\quad\mbox{ if a person is alive at age \(x^-\)}\\0\quad\mbox{ otherwise}\end{cases}\]

where \(x^-\) means immediately before age \(x\) (never mind the asterisk for now). When something keeps cropping up in any branch of mathematics or statistics, there are usually good reasons, and this is no exception. Here are some:

**Written by:**Angus Macdonald

**Tags:**Filter information matrix by tag: left-truncation, Filter information matrix by tag: right-censoring, Filter information matrix by tag: Poisson distribution

### Compare and contrast: VaR v. CTE

**Written by:**Stephen Richards

**Tags:**Filter information matrix by tag: conditional tail expectation, Filter information matrix by tag: SST, Filter information matrix by tag: quantile, Filter information matrix by tag: percentile

### Up close and intimate with the APCI model

This blog brings together two pieces of work. The first is the paper we presented to the Institute and Faculty of Actuaries, *"A stochastic implementation of the APCI model for mortality projections"*, which will appear in the British Actuarial Journal. The second is a previous blog where I examined the role of constraints in models of mortality.

**Written by:**Iain Currie

**Tags:**Filter information matrix by tag: APCI, Filter information matrix by tag: identifiability constraints