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Constraints and the R language

This is the fourth and final blog on the use of constraints in the modelling and forecasting of mortality. The previous three blogs (herehere and here) demonstrated that there is no need to worry about which linear constraints to use: the fitted values of mortality and crucially their forecast values always come out the same.

Written by: Iain CurrieTags: Filter information matrix by tag: identifiability constraints, Filter information matrix by tag: R language

Mortality by the book

Our book, Modelling Mortality with Actuarial Applications, will appear in Spring 2018.  I wrote the second of the three parts, where I describe the modelling and forecasting of aggregate mortality data, such as provided by the Office for National Statistics, the Human Mortality Database or indeed by any insurer whose own data is suitable.
Written by: Iain CurrieTags: Filter information matrix by tag: GLM, Filter information matrix by tag: mortality projections, Filter information matrix by tag: R language

Quantiles and percentiles

Quantiles are points taken at regular intervals from the cumulative distribution function of a random variable. They are generally described as q-quantiles, where q specifies the number of intervals which are separated by q−1 points.
Written by: Stephen RichardsTags: Filter information matrix by tag: quantile, Filter information matrix by tag: percentile, Filter information matrix by tag: Solvency II, Filter information matrix by tag: Excel, Filter information matrix by tag: R language