incrExplor {ProfileLadder} | R Documentation |
Exploratory Function for Run-Off Triangle Increments
Description
The function takes a cumulative or incremental run-off triangle (partially or
completely observed) and provides some basic exploratory and graphical
inspection of the observed incremental payments. The function serves as
a useful tool for a user-based insight when manualy defining the states of
the Markov Chain that is used to drive the reserve prediction in the MACRAME
algorithm implemented in the function mcReserve()
.
Usage
incrExplor(
triangle,
method = c("median", "mean", "max", "min"),
out = 1,
states = NULL,
breaks = NULL
)
Arguments
triangle |
cumulative or incremental run-off triangle (an object of the
class |
method |
method form |
out |
integer value (or a vector of integers) to indicate which columns
of the run-off triangle should be excluded
from the exploratory analysis of the increments. By DEFAULT, the first
incremental payments—i.e., the first column of the run-off triangle—are
not considered ( |
states |
either an integer value to indicate an explicit number of the
Markov chain states to be used or a vector of explicit Markov chain states
can be provided. The DEFAULT option ( |
breaks |
numeric vector of explicit (unique and monotonously increasing)
break points to define the bins for the run-off triangle increments.
If |
Value
An object of the class mcSetup
with the following elements:
incrTriangle |
an object of the class |
triangleType |
type of the input run-off triangle provided for the input
object |
defaultStates |
the data-driven set of explicit states as used (by DEFAULT)
by the |
defaultBreaks |
the set of explicit data-driven breaks as used (by DEFAULT)
by the |
increments |
table with basic empirical characteristics of the increments
of the input run-off triangle (without the first origin payments—the values
in the first column of the run-off triangle). Two sets of increments are provided:
the raw incremental payments in the first row of the table and the standardized
increments (i.e., row incremental payments divided by the maximum payment within
the row (while not considering the columns specified by the |
userDefined |
a list with all information regarding the USER modified input
(numeric vector |
References
Maciak, M., Mizera, I., and Pešta, M. (2022). Functional Profile Techniques for Claims Reserving. ASTIN Bulletin, 52(2), 449-482. DOI:10.1017/asb.2022.4
See Also
Examples
data(CameronMutual)
## default Markov Chain states with (roughly) equally occupied bins
incrExplor(CameronMutual)
## five Markov Chain states (with roughly equally occupied bins)
incrExplor(CameronMutual, states = 5)
## explicitly defined breaks for five increment bins while the Markov states
## are obtained as medians of the increments within each bin
incrExplor(CameronMutual, breaks = c(20, 500, 1000, 2000))
## explicitly defined breaks for five bins and the Markov states
## are given as the maximum increments within each bin
incrExplor(CameronMutual, breaks = c(20, 500, 1000, 2000), method = "max")
## manually defined breaks for the bins and the corresponding states
## exactly one state must be within each break
incrExplor(CameronMutual, breaks = c(20, 500, 1000),
states = c(10, 250, 800, 1500))