Chainladder

New Features

* New generic function CDR to estimate the one year claims development
result. S3 methods for the Mack and bootstrap model have been
added already:
- CDR.MackChainLadder to estimate the one year claims
development result of the Mack model without tail factor,
based on papers by Merz & Wuthrich (2008, 2014)
- CDR.BootChainLadder to estimate the one year claims
development result of the bootstrap model, using ideas and code
by Giuseppe Crupi.

* New function tweedieReserve to estimate reserves in a GLM framework,
including the one year claims development result.

* Package vignette has new chapter 'One Year Claims Development
Result'.

* New example data MW2008 and MW2014 form the Merz & Wuthrich (2008, 2014)
papers

Changes

* Source code development moved from Google Code to GitHub:
https://github.com/mages/ChainLadder

* as.data.frame.triangle now gives warning message when dev. period
is a character

* Alessandro Carrato, Giuseppe Crupi and Mario Wuthrich have been
added as authors, thanks to their major contribution to code and
documentation

* Christophe Dutang, Arnaud Lacoume and Arthur Charpentier have been
added as contributors, thanks to their feedback, guidance and
code contribution

User-visible changes

* 'MackChainLadder' has new argument 'alpha' as an additional
weighting parameter. As a result, the argument 'weights' is now
just that, weights should be between 0 and 1.
The argument 'alpha' describes the different chain ladder
age-to-age factors:
The default for alpha for all development periods is 1. See
Mack's 1999 paper:
alpha=1 gives the historical chain ladder age-to-age factors,
alpha=0 gives the straight average of the observed individual
development factors and
alpha=2 is the result of an ordinary regression with intercept 0.

* Basic 'chainladder' function now available using linear
models. See ?chainladder for more information.

* More examples for 'MackChainLadder' demonstrate how to apply the
MackChainLadder over several triangles in 'one-line'.

* 'as.data.frame.triangle' has new argument 'lob' (e.g. line of
business) which allows to set an additional label column in the
data frame output.

Bug fixes

* 'MackChainLadder': Latest position of incomplete triangles were
in some cases not returned correctly. Thanks to Ben Escoto for
reporting and providing a patch.

* 'MackChainLadder':
- Mack.S.E was not correctly calculated for non-standard chain
ladder age-to-age factors (e.g. straight averages or ordinary
regression through the origin) due the missing argument for 'alpha'.
- Chain ladder age-to-age factors were always applied to diagonal
elements to calculate forecasts, although data in sub-diagonal
triangle could exist. Many thanks to Przemyslaw Sloma for
reporting those issues.

New Features

* New triangle class with S3 methods for plot, print and conversion
from triangles to data.frames and vis versa

* New utility functions 'incr2cum' and 'cum2incr' to convert
incremental triangles into cumulative triangles and vis
versa. Thanks to Chritophe Dutang.
* New logical argument lattice for plot.MackChainLadder (and
plot.triangle), which allows to plot developments by origin period
in separate panels.

Bug fixes

* 'MunichChainLadder': tail factors were not accepted. Thanks to
Stefan Pohl for reporting this issue.

Bug fixes

* 'MackChainLadder': 'F.se'[ultimate] was calculated of the ultimate
column instead of the latest paid.

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.