Chainladder

User-visible changes

* 'MackChainLadder' has new arguments 'tail.sigma' and 'tail.se' to
provide estimates of the variability for a given tail factor.

Bug fixes

* 'MackChainLadder': calculation of 'Mack.S.E' did not use an
ultimate sigma factor to estimate 'Mack.S.E' when a tail factor >
1 was provided (Thanks to Mark Hoffmann for reporting this issue).

New Features

* The list output of the MackChainLadder function now includes
the parameter risk and process risk breakdowns of the total risk
estimate for the sum of projected losses across all origin years
by development age.
* The Mack Method's recursive parameter risk calculation now enables
Dr. Mack's original two-term formula (the default) and optionally
the three-term formula found in Murphy's 1994 paper and in the
2006 paper by Buchwalder, Buhlmann, Merz, and Wuthrich.
* A few more Mack Method examples.

Bug Fixes

* The phi-scaling factor in BootChainLadder was incorrect.
Instead of calculating the number of data items in the upper left
triangle as n*(n+1)/2, n*(n-1)/2 was used. Thanks to Thomas
Girodot for reporting this bug.

New Features

* The function "getLatestCumulative" adds attributes to
the result
- names = origin (rownames) from the Triangle
- rowsname = name of row dimension of Triangle
- colnames = dev (colnames) from Triangle
- colsname = name of the column dimension of Triangle
The function has an additional argument, na.values, a
vector of values (e.g., zero) that are synonymous with NA
when searching for the rightmost non-NA value
* as.triangle.data.frame now aggregates multiple data.frame
records when more than one (origin, dev) observation is
found (the previous version took the first observation).

Changes

* The vignette has been updated with sections on Multivariate
chain-ladder, Clark's method and Generalised linear model methods
* MunichChainLadder no longer accepts triangles with more rows than
columns as the function is not laid out for such data sets
yet. Thanks to Ben Escoto for highlighting this issue.

New Features

* The function "glmReserve" now simulates predictive distributions
of the loss reserves when bootstrapping is used.
* "glmReserve" allows the variance function of the compound Poisson
distribution to be estimated from the data, using the estimation
method provided by the "cplm" package.
* We offer a new function "MultiChainLadder2" to fit several commonly
used multivariate chain ladder models, which is much easier to use.

Changes

* The output from "glmReserve" is made to be of class "glmReserve", instead
of class "glm" used in previous versions.
* Fix bugs when exposure is included in "glmReserve". Thanks to
Alessandro Carrato for reporting this bug.
* The "mse.method" argument in "glmReserve" supports partial match.
* Dramatic improvement on the documentation of "MultiChainLadder".
* Complete the sections of "MultiChainLadder" and "glmReserve" in
the vignettes.

New Features

* We started writing a vignette. The current version is still draft
and far from complete. Feedback will be much appreciated.

Changes

* Removed .Internal call to make ChainLadder compliant with R 2.15.0
* Changed argument "t" in plot.triangle to "type" in order to be
consistent with plot.default

Bug Fixes

* as.triangle() gave triangles back, with development periods not
ordered, when the input data frame had unordered development
periods in different units, e.g. dev=c(1,100,10)
Thanks to Ben Escoto for reporting this issue.