Chainladder

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.

* Internal changes to plot.MackChainLadder to pass new checks
introduced by R 2.14.0.
* Commented out unnecessary creation of 'io' matrix in ClarkCapeCod
function. Allows for analysis of very large matrices for CapeCod
without running out of RAM. 'io' matrix is an integral part of
ClarkLDF, and so remains in that function.
* plot.clark method
- Removed "conclusion" stated in QQplot of clark methods.
- Restore 'par' settings upon exit
- Slight change to the title
* Reduced the minimum 'theta' boundary for weibull growth function
* Added warnings to as.triangle if origin dev. period are not numeric

New Features

* New function glmReserve, which implements loss reserving models
within the generalized linear model framework following a paper by
England P. and Verrall R. (1999)