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Great Expectations

When fitting statistical models, a number of features are commonly assumed by users. Chief amongst these assumptions is that the expected number of events according to the model will equal the actual number in the data. This strikes most people as a thoroughly reasonable expectation. Reasonable, but often wrong.

Written by: Stephen RichardsTags: GLM

Confounding compounding

Earlier posts discussed the importance of deduplication in annuity portfolios and pension schemes and some of the issues around the deduplication of names, specifically the use of double metaphone to look through common variant spellings of the surname or family name.
Written by: Gavin RitchieTags: deduplication, duplicates

A likely story

The foundation for most modern statistical inference is the log-likelihood function.  By maximising the value of this function, we find the maximum-likelihood estimate (MLE) for a given parameter, i.e. the most likely value given the model and data.  For models with more than one parameter, we find the set of values which jointly maximise the log-likelihood.

Written by: Stephen RichardsTags: Makeham, log-likelihood

Do we need standard tables any more?

Actuaries are long used to using standard tables. In the UK these are created by the Continuous Mortality Investigation Bureau (CMIB), and the use of certain tables is often prescribed in legislation. As actuaries increasingly move to using statistical models for mortality, it is perhaps natural that they should first consider incorporating standard tables into these models. But are standard tables necessary, or even useful, in such a context?

Written by: Stephen RichardsTags: standard table, GLM, survival models

New SAPS tables

On 31st October 2008 the CMIB published the new SAPS S1 mortality tables based on the mortality of defined-benefit pension schemes. These tables follow the previous release of the '00 Series' mortality tables based on the mortality of life-office pensioners. 
Written by: Stephen RichardsTags: standard table

Why we don't fit models in Excel

Actuaries are very heavy users of spreadsheets, especially Microsoft® Excel.  One question we are occasionally asked is why we wrote our software in C++, instead of letting people have direct access to our code as a spreadsheet. 
Written by: Stephen RichardsTags: spreadsheet, Excel, C++

Competing risks

Survival models are models for continuous risk, e.g. the force of mortality, μx.  We showed in an earlier post why this is more powerful and efficient than modelling the rate of mortality, qx
Written by: Stephen RichardsTags: force of mortality

Modelling and the maple leaf

We get a lot of interest in our software from Canada. We don't know specifically why this might be — despite that fact that two of our founders are Scottish, we are not aware of any distant relatives still panning for gold out there.
Written by: Gavin RitchieTags: postcodes, Canada, geodemographics

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Not all security strategies need be as dramatic as those proposed by Mission Impossible, but anyone offering SaaS needs to ensure data is accessible by only authorised users.
Written by: Gavin RitchieTags: security, encryption, technology

Parallel processing

A colleague of mine once described parallel processing as the "work of the devil". I don't know if I'd go quite this far — this statement was made in the early nineties, when technology was that little bit less advanced than it is today.
Written by: Gavin RitchieTags: parallel processing, technology