# Information Matrix

## Filter Information matrix

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### Mortality down under

Different countries have different mortality characteristics, and this is true even where countries have similar levels of wealth and development.  However, different countries also have shared mortality characteristics, and one of these is seasonal variation.
Written by: Stephen Richards

### 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:

Written by: Angus Macdonald

### Label without a cause

To talk informally about a concept, we need only give it a recognisable name. For example, we use the label "medical error" and we all know what is meant - or at least we think we do.
Written by: Gavin Ritchie

### A shaky foundation?

As with anything that must combine reliable data with hard maths and sound judgement, forecasting mortality is difficult.
Written by: Gavin Ritchie

### Correlation complications

A basic result in probability theory is that the variance of the sum of two random variables is not necessarily the same as the sum of their variances.
Written by: Stephen Richards

### Summary judgement

In previous posts we have looked at problems with the quality and reliability of cause-of-death data and a list of hurdles for mortality projections based on such data.  One other issue is that of detail.
Written by: Stephen Richards

### Shifting sands

In civil engineering, no building can be sounder than the foundation on which it rests.  A similar comment applies to statistical analysis, which is obviously limited by the quality of the underlying data.
Written by: Stephen Richards

### Seven questions for projections by cause of death

I have written several times about the challenges in creating mortality projections based on cause-of-death data.  Those interested in the details can consult my recent paper published in a special edition of the British Actuarial Journal.
Written by: Stephen Richards

### Cutting the bias

With the exception of dressmaking, bias is generally undesirable. This is particularly the case when projecting future mortality rates for reserving for pension liabilities.
Written by: Stephen Richards

### For the record

Stephen has written about the challenges in using population cause-of-death data for mortality analysis and forecasting. Another potential source of data is computerised patient records such as the General Practice Research Database (GPRD).
Written by: Dr Chris Martin