
Print results of Clark methods
print.clark.rd
Functions to print the results of the ClarkLDF and ClarkCapeCod methods.
Usage
<!-- %- \method{print}{clark}(x, \dots) -->
# S3 method for ClarkLDF
print(x, Amountdigits=0, LDFdigits=3, CVdigits=3,
row.names = FALSE, ...)
# S3 method for ClarkCapeCod
print(x, Amountdigits=0, ELRdigits=3, Gdigits=4, CVdigits=3,
row.names = FALSE, ...)
Arguments
- x
object resulting from a run of the ClarkLDF or ClarkCapeCod function.
- Amountdigits
number of digits to display to the right of the decimal point for "amount" columns
- LDFdigits
number of digits to display to the right of the decimal point for the loss development factor (LDF) column
- CVdigits
number of digits to display to the right of the decimal point for the coefficient of variation (CV) column
- ELRdigits
number of digits to display to the right of the decimal point for the expected loss ratio (ELR) column
- Gdigits
number of digits to display to the right of the decimal point for the "growth function factor" column; default of 4 conforms with the table on pp. 67, 68 of Clark's paper
- row.names
logical (or character vector), indicating whether (or what) row names should be printed (same as for
print.data.frame
)- ...
further arguments passed to
print
Details
Display the default information in "pretty format" resulting from a run of the "LDF Method" or "Cape Cod Method" -- a "Development-type" exhibit for Clark's "LDF Method," a "Bornhuetter-Ferguson-type" exhibit for Clark's "Cape Cod Method."
As usual, typing the name of such an object at the console
invokes its print
method.
Value
data.frame
s whose columns are the character
representation
of their respective summary.ClarkLDF
data.frame
s.
References
Clark, David R., "LDF Curve-Fitting and Stochastic Reserving: A Maximum Likelihood Approach", Casualty Actuarial Society Forum, Fall, 2003
Examples
X <- GenIns
colnames(X) <- 12*as.numeric(colnames(X))
y <- ClarkCapeCod(X, Premium=10000000+400000*0:9, maxage=240)
summary(y)
#> Origin CurrentValue Premium ELR FutureGrowthFactor FutureValue
#> 1 1 3901463 1.00e+07 0.597026 0.1303902 778463.4
#> 2 2 5339085 1.04e+07 0.597026 0.1594364 989952.1
#> 3 3 4909315 1.08e+07 0.597026 0.1950165 1257443.3
#> 4 4 4588268 1.12e+07 0.597026 0.2391815 1599332.9
#> 5 5 3873311 1.16e+07 0.597026 0.2947437 2041248.2
#> 6 6 3691712 1.20e+07 0.597026 0.3654987 2618546.9
#> 7 7 3483130 1.24e+07 0.597026 0.4562722 3377839.6
#> 8 8 2864498 1.28e+07 0.597026 0.5720671 4371698.3
#> 9 9 1363294 1.32e+07 0.597026 0.7137828 5625139.6
#> 10 10 344014 1.36e+07 0.597026 0.8617075 6996681.1
#> Total Total 34358090 1.18e+08 NA NA 29656345.3
#> UltimateValue StdError CV
#> 1 4679926 269248.7 0.3458721
#> 2 6329037 311328.7 0.3144887
#> 3 6166758 358975.2 0.2854803
#> 4 6187601 412520.2 0.2579326
#> 5 5914559 471780.8 0.2311237
#> 6 6310259 535626.0 0.2045509
#> 7 6860970 601534.4 0.1780826
#> 8 7236196 665860.7 0.1523117
#> 9 6988434 726347.9 0.1291253
#> 10 7340695 786672.0 0.1124350
#> Total 64014435 3402778.6 0.1147403
print(y) # (or simply 'y') Same as summary(y) but with "pretty formats"
#> Origin CurrentValue Premium ELR FutureGrowthFactor FutureValue
#> 1 3,901,463 10,000,000 0.597 0.1304 778,463
#> 2 5,339,085 10,400,000 0.597 0.1594 989,952
#> 3 4,909,315 10,800,000 0.597 0.1950 1,257,443
#> 4 4,588,268 11,200,000 0.597 0.2392 1,599,333
#> 5 3,873,311 11,600,000 0.597 0.2947 2,041,248
#> 6 3,691,712 12,000,000 0.597 0.3655 2,618,547
#> 7 3,483,130 12,400,000 0.597 0.4563 3,377,840
#> 8 2,864,498 12,800,000 0.597 0.5721 4,371,698
#> 9 1,363,294 13,200,000 0.597 0.7138 5,625,140
#> 10 344,014 13,600,000 0.597 0.8617 6,996,681
#> Total 34,358,090 118,000,000 29,656,345
#> UltimateValue StdError CV%
#> 4,679,926 269,249 34.6
#> 6,329,037 311,329 31.4
#> 6,166,758 358,975 28.5
#> 6,187,601 412,520 25.8
#> 5,914,559 471,781 23.1
#> 6,310,259 535,626 20.5
#> 6,860,970 601,534 17.8
#> 7,236,196 665,861 15.2
#> 6,988,434 726,348 12.9
#> 7,340,695 786,672 11.2
#> 64,014,435 3,402,779 11.5
## Greater growth factors when projecting to infinite maximum age
ClarkCapeCod(X, Premium=10000000+400000*0:9, maxage=Inf)
#> Origin CurrentValue Premium ELR FutureGrowthFactor FutureValue
#> 1 3,901,463 10,000,000 0.597 0.2217 1,323,698
#> 2 5,339,085 10,400,000 0.597 0.2508 1,556,996
#> 3 4,909,315 10,800,000 0.597 0.2863 1,846,297
#> 4 4,588,268 11,200,000 0.597 0.3305 2,209,996
#> 5 3,873,311 11,600,000 0.597 0.3861 2,673,721
#> 6 3,691,712 12,000,000 0.597 0.4568 3,272,829
#> 7 3,483,130 12,400,000 0.597 0.5476 4,053,931
#> 8 2,864,498 12,800,000 0.597 0.6634 5,069,599
#> 9 1,363,294 13,200,000 0.597 0.8051 6,344,850
#> 10 344,014 13,600,000 0.597 0.9530 7,738,201
#> Total 34,358,090 118,000,000 36,090,118
#> UltimateValue StdError CV%
#> 5,225,161 443,978 33.5
#> 6,896,081 489,929 31.5
#> 6,755,612 541,157 29.3
#> 6,798,264 597,696 27.0
#> 6,547,032 658,893 24.6
#> 6,964,541 722,850 22.1
#> 7,537,061 785,803 19.4
#> 7,934,097 842,378 16.6
#> 7,708,144 889,806 14.0
#> 8,082,215 941,203 12.2
#> 70,448,208 5,378,616 14.9