NEWS
ChainLadder 0.2.19 (2024-07-21)
- Fixed links in documentation that had references to a functions from different R packages, as reported by CRAN checks
ChainLadder 0.2.18 (2023-06-27)
- Changes to the Matrix package (in 1.5-5) have impacted the MultiChainLadder2 function, which need to be resolved. In some cases the function fails when the data results in near-singular matrix inversions
ChainLadder 0.2.17 (2023-01-12)
- New seed argument for BootChainLadder to set an optional seed for the random generator
ChainLadder 0.2.16 (2022-08-23)
- New weights argument for MuinchChainLadder
- Fixed typo checking for weight argument in glmReserve. Thanks to Kennedy Mwavu for reporting this issue
- Fixed weights in CDR.MackChainLadder. Thanks to Giorgia Chieruzzi for contributing the patch
ChainLadder 0.2.15 (2022-01-09)
- Started using pkgdown to create package website
- Added ChainLadder hexagon graphic
- Moved vignettes/NEWS.Rmd to NEW.md to autogenerate changelog with pkgdown
- Clarified how to extract MackChainLadder objects in package vignette
ChainLadder 0.2.14 (2021-11-11)
- Updated package dependencies to address a warning from CRAN
ChainLadder 0.2.13 (2021-10-06)
- Updated URLs in the bibliography of the package vignette and help files
ChainLadder 0.2.12 (2021-01-05)
- Moved continuous integration testing from TravisCI to GitHub Actions
- Changed vignette format from Sweave to RMarkdown to facilitate easier
testing using GitHub Actions
ChainLadder 0.2.11 (2020-02-10)
- Fixed as.triangle for a 'long' data set, when input data had missing values.
Thanks to Dimitri Minassian for reporting this issue.
- Fixed standard error estimation in MackChainLadder when tail factor > 1
and alpha = 2. Thanks to Valentin Cornaciu for reporting this issue.
ChainLadder 0.2.10 (2019-05-27)
- Added Berquist-Sherman Paid Claim Development Adjustment methods to adjust
paid claims based on the underlying relation between paid and closed claims.
- Added tests to check calendar year effect, correlation between development
factors and inflation.
Thanks to Marco De Virgilis.
ChainLadder 0.2.9 (2018-12-06)
- Fix to as.triangle.data.frame. The labels of origin and development period
were mixed up with the move away from reshape2 to aggregate in version 0.2.8.
Thanks to Edward Tasker for reporting this issue.
ChainLadder 0.2.8 (2018-11-12)
- Fix to print statements to align them with the generic print methods.
Thanks to Markus Senn
- Clarified how the 'weights' argument in chainladder and MackChainLadder
can be used
- Removed dependency on reshape2 as it has been deprecated
ChainLadder 0.2.7 (2018-10-16)
- New quantile method for 'MackChainLadder' andv function QuantileIFRS17
to estimate the IFRS 17 Risk Adjustment. Thanks to Eric Dal Moro and Yuriy
Krvavych
ChainLadder 0.2.6 (2018-05-29)
- New function 'triangle' to create a triangle from the given set of vectors
of observed data. Thanks to Vincent Goulet
ChainLadder 0.2.5 (2017-10-19)
- Fixed bug in Mack.S.E function when "sigma[i - 2]^2" is zero.
Thanks to Patrick Green for reporting and fixing the issue.
ChainLadder 0.2.4 (2017-01-01)
- Fixed meta information of NEWS vignette, so it will be shown
as NEWS on CRAN
ChainLadder 0.2.3 (2016-10-21)
Changes
NEWS file
Moved NEWS file to Markdown format.
Triangles may now have non-numeric rownames
Previously it was required that the row and column names of a triangle be convertible to numeric, although that "requirement" did not always cause a problem.
For example, the following sets the rownames of GenIns to the beginning Date
of the accident year.
x <- GenIns
rownames(x) <- paste0(2001:2010, "-01-01")
A plot with the lattice=TRUE option, which previously would blow up,
now displays with nice headings.
plot(x, lattice=TRUE)
It can often be useful to have "origin" values that are
not necessarily convertible to numeric.
For example, suppose you have a table of claim detail at various evaluation dates.
Invariably, such a table will have a Date field holding the date of loss.
It would be nice to be able to summarize that data by accident year "cuts".
It turns out there's a builtin function in R that will get you most of the way there. It's called 'cut'.
Here we take the GenIns data in long format and
generate 50 claims per accident period.
We assign each claim a random date within the year.
The incurred (or paid) "value" given is a random perturbation of one-fiftieth of
GenInsLong$value.
We accumulate the detail into an accident year triangle using
ChainLadder's as.triangle method.
The summarized triangle displayed at the end is very similar to GenIns, and
has informative row labels.
x <- GenInsLong
# start off y with x's headings
y <- x[0,]
names(y)[1] <- "lossdate"
set.seed(1234)
n = 50 # number of simulated claims per accident perior
for (i in 1:nrow(x)) {
y <- rbind(y,
data.frame(
lossdate = as.Date(
as.numeric(as.Date(paste0(x[i, "accyear"]+2000, "-01-01"))) +
round(runif(n, 0, 364),0), origin = "1970-01-01"),
devyear = x[i, "devyear"],
incurred.claims = rnorm(n, mean = x[i, "incurred claims"] / n,
sd = x[i, "incurred claims"]/(10*n))
))
}
# here's the magic cut
y$ay <- cut(y$lossdate, breaks = "years")
# this summarized triangle is very similar to GenIns
as.triangle(y, origin = "ay", dev = "devyear", value = "incurred.claims")
The user is encouraged to experiment with other cut's --
e.g., breaks = "quarters" will generate accident quarter triangles.
New as.LongTriangle function
A new function, as.LongTriangle, will convert a triangle
from "wide" (matrix) format to "long" (data.frame) format.
This differs from ChainLadder's
as.data.frame.triangle method in that the
rownames and colnames of Triangle are stored as factors.
This feature can be particularly important when plotting a triangle
because the order of the "origin" and "dev" values is important.
Additionally, the columns of the resulting data frame
may be renamed from the default values ("origin", "dev", and "value")
using the "varnames" argument for "origin"/"dev"
and the "value.name" argument for "value".
In the following example, the GenIns triangle in ChainLadder
is converted to a data.frame with non-default names:
GenLong <- as.LongTriangle(GenIns,
varnames = c("accident year", "development age"),
value.name = "Incurred Loss")
In the following plot,
the last accident year and the last development age are shown last,
rather than second as they would have been if displayed alphabetically
(ggplot's default for character data):
library(ggplot2)
ggplot(GenLong, aes(x=`development age`, y = `Incurred Loss`,
group = `accident year`, color = `accident year`)) +
geom_line()
glmReserve "exposure" attribute may now have names
Previously, when an "exposure" attribute was assigned to a triangle
for use with glmReserve, it was assumed/expected that the user would supply the values in the same order as the accident years.
Then, behind the scenes, glmReserve would use an arithmetic formula to match
the exposure with the appropriate accident year using the numeric "origin" values
after the triangle had been converted to long format.
glmReserve now allows for "exposure" to have "names"
that coincide with the rownames of the triangle,
which are used to match to origin in long format.
Here is an example, newly found in ?glmReserve.
GenIns2 <- GenIns
rownames(GenIns2) <- paste0(2001:2010, "-01-01")
expos <- (7 + 1:10 * 0.4) * 10
names(expos) <- rownames(GenIns2)
attr(GenIns2, "exposure") <- expos
glmReserve(GenIns2)
glmReserve adds support for negative binomial GLM
The glmReserve function now supports the negative binomial GLM,
a more natural way to model over-dispersion in count data.
The model is fitted through the glm.nb function from the MASS package.
To fit the negative binomial GLM to the loss triangle,
simply set nb = TRUE in calling the glmReserve function:
(fit6 <- glmReserve(GenIns, nb = TRUE))
New unit tests
New files in the /inst/unittests/ folder can be used for
future enhancements
- runit.Triangles.R for Triangles.R
- runit.glmReserve.R for glmReserve.R
Contributors of new contributions to those R files are encouraged
to utilize those runit scripts for testing,
and, of course, add other runit scripts as warrantted.
Clarified warnings issued by MackChainLadder
By default, R's lm method generates a warning when it detects
an "essentially perfect fit".
This can happen when one column of a triangle is identical to the previous column;
i.e., when all link ratios in a column are the same.
In the example below, the second column is a fixed constant, 1.05,
times the first column.
ChainLadder previously issued the lm warning below.
x <- matrix(byrow = TRUE, nrow = 4, ncol = 4,
dimnames = list(origin = LETTERS[1:4], dev = 1:4),
data = c(
100, 105, 106, 106.5,
200, 210, 211, NA,
300, 315, NA, NA,
400, NA, NA, NA)
)
mcl <- MackChainLadder(x, est.sigma = "Mack")
Warning messages:
1: In summary.lm(x) : essentially perfect fit: summary may be unreliable
2: In summary.lm(x) : essentially perfect fit: summary may be unreliable
3: In summary.lm(x) : essentially perfect fit: summary may be unreliable
which may have raised a concern with the user when none was warranted.
Now ChainLadder issues an "informational warning":
x <- matrix(byrow = TRUE, nrow = 4, ncol = 4,
dimnames = list(origin = LETTERS[1:4], dev = 1:4),
data = c(
100, 105, 106, 106.5,
200, 210, 211, NA,
300, 315, NA, NA,
400, NA, NA, NA)
)
mcl <- MackChainLadder(x, est.sigma = "Mack")
Bug fixes
Fixed tail extrapolation
Fixed tail extrapolation in Vignette.
(Thanks to Mark Lee.)
- Fixed summary calls.
- Updated documentation for weights parameter of chainladder method.
- Fixes for tail extrapolation in Vignette and Chainladder
- The calculation for the tail log-linear extrapolation given in
the vignette had a minor error. This has been corrected,
and the result now agrees with the results of
MackChainLadder(RAA, tail=TRUE).
- The calculation of the tail using the log-linear extrapolation
in ChainLadder.R had a potential error - when clratios has
values of less than unity they are dropped, but the extrapolation
was started from a quantity indexed by the length of f, not
the value of fn. This changes the results if clratios has a
pattern like e.,g.: ... 1.1, 0.98,1.01,0.005 (i.e. a link ratio
less than unity which is not the last value)
- Minor fix to the comments in ChainLadder.R and MackChainLadder.R,
fixing notation for alpha which is now consistent with the
documentation and Mack's original paper.
ChainLadder 0.2.2 (2015-08-31)
ChainLadder 0.2.1 (2015-07-11)
New Features
Changes
ChainLadder 0.2.0 (2015-03-04)
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
ChainLadder 0.1.9 (2014-12-20)
Changes
- Updated README and DESCRIPTION file to comply with changes of
CRAN policy.
ChainLadder 0.1.8 (2014-08-23)
Bug Fixes
- BootChainLadder produced warnings for triangles that had static
developments when the argument process.distr was set to "od.pois".
- as.triangle.data.frame didn't work for a data.frame less than three rows
- Arguments xlab and ylab were not passed through in plot.triangle, when
lattice=TRUE
ChainLadder 0.1.7 (2013-09-28)
Changes
- The glmReserve function currently doesn't allow the parameter var.power
to be set to NULL, which would have called the cpglm function of the
cplm package. The cplm package is due to dependency issues with lme4
no longer available via CRAN.
ChainLadder 0.1.6 (2013-08-09)
New Features
-
A new function, CLFMdelta, finds the value of
delta such that the model coefficients resulting from
the 'chainladder' function with that value for argument delta are
consistent with an input vector of 'selected' age-to-age factors,
subject to restrictions on the 'selected' factors relative to
the input 'Triangle'. See the paper
"A Family of Chain-Ladder Factor Models for Selected Link Ratios"
by Bardis, Majidi, Murphy, Variance Journal
-
A new 'coef' method returns the age-to-age factor coefficients of
the regression models estimated by the 'chainladder' function.
-
Exports a function "LRfunction" that calculates a Triangle's
link ratio function and can be used to plot the space of
"reasonable link ratio selections" per the CLFM paper.
Changes
- Removed some package dependencies in DESCRIPTION and moved them
to Imports.
ChainLadder 0.1.5-6 (2013-03-17)
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.
ChainLadder 0.1.5-5
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.
ChainLadder 0.1.5-4 (2012-11-11)
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.
ChainLadder 0.1.5-3
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.
ChainLadder 0.1.5-2 (2012-03-25)
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.
ChainLadder 0.1.5-1 (2011-11-12)
- 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
ChainLadder 0.1.5-0 (2011-08-29)
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)
ChainLadder 0.1.4-4
- Minor changes to reflect a more rigours package build process for
R >= 2.14.0
- Start up message uses now packageStartupMessage rather than cat to
allow the message to be suppressed.
ChainLadder 0.1.4-3 (2011-01-18)
New Features
- ClarkLDF and ClarkCapeCod functions were reorganized to clarify
the delivery and presentation of the methods' results
- Individual components now contain distinct values within
Clark's methodologies
- 'summary' methods produce "reports" that display results in
the form of typical loss development and Bornhuetter-Ferguson
exhibits
- "Table" functions now produce the results as shown in the
tables on pp. 64, 65 and 68 of Clark's paper
- A 'vcov' method produces the covariance matrix of the
estimated parameters
- An 'ata' function exists to calculate the "age-to-age" development
factors of a loss "triangle", as well as the simple and volume
weighted averages
ChainLadder 0.1.4-2 (2011-01-03)
Bug fixes
- The TruncatedGrowth function value under the Clark Cape Cod method
was incorrectly printed in the Table68 data.frame when the
calculations were to be based on the average date of loss (argument
adol=TRUE). The underlying calculations used the correct adol
adjustment, only the printed output was incorrect.
ChainLadder 0.1.4-1
New Features
Bug fixes
ChainLadder 0.1.4-0 (2010-11-11)
New Features
ChainLadder 0.1.3-4 (2010-10-19)
Bug fixes
- 'residuals.MackChainLadder': Zero weights applied to
MackChainLadder caused an error. Thanks to Ernesto Schirmacher for
reporting this bug.
ChainLadder 0.1.3-3 (2010-05-16)
New Features
- New multivariate chain ladder function 'MultiChainLadder' by Wayne
(Yanwei) Zhang [email protected]
- New function 'getLatestCumulative' available. It returns for a
given triangle the most recent values for each origin period.
- New demos! Type demo(package='ChainLadder') for more information.
- Demos exist for the following topics: ChainLadder,
MackChainLadder, DatabaseExamples, MSOffice, MultiChainLadder
- New SWord example file ChainLadder_SWord_Example.doc, which
demonstrates how R code snippets can be integrated into a Word
file.
The following R command system.file("SWord",
package="ChainLadder") will show the directory of the file.
User-visible changes
- The examples in MackChainLadder and ChainLadder-package have been
shortened and demo files have been created instead.
The examples focus on the syntax of the function calls, while the
demos give more detailed information on how you might want to use
the functions in a business context.
Bug fixes
- 'plot.MunichChainLadder': The labels of the axis of the residuals
plots where the mixed up.
Thanks to Ben Escoto for reporting this issue.
- 'estimate.sigma' didn't check for sigma>0 before applying a
log-linear regression. Thanks to Dan Murphy reporting this bug.
ChainLadder 0.1.2-13 (2009-11-24)
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
ChainLadder 0.1.2-12
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.
ChainLadder 0.1.2-11 (2009-03-28)
Bug fixes
- 'MackChainLadder': 'F.se'[ultimate] was calculated of the ultimate
column instead of the latest paid.
ChainLadder 0.1.2-10 (2009-03-27)
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).
ChainLadder 0.1.2-9 (2009-02-01)
User-visible changes
- Updated documentation to work with new Rd-file parser
(R version >= 2.9.0)
- Updated documentation for 'ABC' data (Thanks to Glen Barnett)
ChainLadder 0.1.2-8 (2008-11-03)
User-visible changes
- Updated documentation for 'MackChainLadder' (Thanks to Daniel Murphy)
ChainLadder 0.1.2-7 (2008-10-24)
User-visible changes
- 'MackChainLadder' gives two more elements back: 'Mack.ProcessRisk'
and 'Mack.ParameterRisk' for the process and parameter risk error
(Thanks to Daniel Murphy)
- In the summary output of 'MackChainLadder' the label 'CV' changed
to 'CV(IBNR)' to clarify that we show the coefficient of variance
of the IBNR.
- 'MackChainLadder' provides new example plots for CV(IBNR)
vs. origin period and CV(Ultimate) vs. origin period
- Updated documentation
ChainLadder 0.1.2-6 (2008-10-14)
User-visible changes
ChainLadder 0.1.2-5 (2008-10-13)
New Features
- New function 'BootChainLadder', based on papers by England and Verrall,
and Barnett and Zehnwirth
- 'MackChainLadder' and 'MunichChainLadder' allow for tail factors
- 'MackChainLadder' estimates the overall standard error for the total IBNR
- New arguments 'tail' and 'est.sigma' for MackChainLadder, to control
the tail factor and the estimation of sigma_{n-1}
- New arguments 'tailP', 'tailI' and 'est.sigmaP', 'est.sigmaI' for
'MunichChainLadder', which are passed on to 'MackChainLadder' to control
the tail factor and the estimation of sigma_{n-1} for the Paid and
Incurred triangle
- 'Mack-, 'Munich-, and 'BootChainLadder' accept (mxn) matrices with m>=n,
e.g more accident years than development years
- New example data sets: 'ABC' (annual run-off triangle of a worker's
compensation portfolio of a large company), 'qpaid', 'qincurred' ('made-up'
data of a quarterly development triangle of annual origin period)
- Triangles with higher development period frequency (e.g quarterly) than
origin period frequency (e.g annual) can be used after being 'blown-up'
to a common period frequency, see the help of 'qpaid'
- 'Mack-, 'Munich- and 'BootChainLadder' accept 'blown-up' triangles of
higher development period frequency than origin period frequency filled
with 'NA', see the help of 'qpaid'
User-visible changes
- summary functions for 'Mack-, 'Munich-, 'BootChainLadder' give all a list
back with two elements: 'ByOrigin' and 'Totals'
- Change of labels: origin years -> origin period and development years ->
development origin
- Coefficient of Variation is abbreviate with 'CV' instead of 'CoV'
- The example spreadsheet 'ChainLadder_in_Excel.xls' has new examples,
including 'BootChainLadder'
- New greeting message after the R-call 'library(ChainLadder)'
- Improved documentation
Bug fixes
- 'MunichChainLadder': calculation of 'lambdaP' and 'lambdI' was incorrect.
Thanks to Beat Huggler for reporting this issue.
ChainLadder 0.1.2-4
- R/BootstrapReserve.R Included all the functions for the BootChainLadder
function. The BootChainLadder procedure provides a predictive
distribution of reserves for a cumulative claims development
triangle.
- R/BootstrapReserve.R, MackChainLadder.R, MunichChainLadder The summary
methods for MackChainLadder, MunichChainLadder, BootChainLadder
give a list back with two elements "ByOrigin" and "Totals"
- R/zzz.R Included a .onLoad function to produce a little message
after the ChainLadder package is loaded.
- Excel/ChainLadder_in_Excel.xls Added new examples for
BootChainLadder and how to use Rapply to call functions from the
ChainLadder package.
ChainLadder 0.1.2-2
- R/MackChainLadder.R Included tail factor estimation. The
function MackChainLadder has a new argument "tail" to either
estimate the tail factor via a log-linear regression or to set it manually.
- data/qpaid.RData, qincurred.RData Added examples of quarterly
development triangles
ChainLadder 0.1.2-0
- R/MackChainLadder.R Prepared the functions Mack.S.E and
Total.Mack.S.E to accept triangles with rows full of NA values.
This might be useful for non quadratic triangles
ChainLadder 0.1.1-5 (2008-05-19)
- R/MackChainLadder.R Bug fix: Function Mack.S.E did not give F.se back,
which is needed by TotalMack.S.E.
Many thanks to Florian Leitenstorfer for reporting this issue.
ChainLadder 0.1.1-4 (2008-05-14)
- inst/Excel/ChainLadder_in_Excel.xls uses now dynamic functions
and shows how to call 'plot' from Excel
- R/MackChainLadderFunctions.R: Changed labels Reserving to IBNR
(=Incurred But Not Reported)
ChainLadder 0.1.1-3 (2008-02-19)
- R/MackChainLadderFunctions.R: Mack.S.E checks now which sigma>0 before log
linear regression of sigma to estimate sigma[n-1]
ChainLadder 0.1.1-2 (2008-02-07)
- R/MackChainLadderFunctions.R: added function
TotalMack.S.E function to estimate the overall standard error for
the reserve. MackChainLadder gives now also the
Total.Mack.S.E. back plus the estimate standard error for all
individual age-to-age factors F.se.
ChainLadder 0.1.1-1 (2007-12-07)