Extract residuals of a MackChainLadder model
residuals.MackChainLadder.RdExtract residuals of a MackChainLadder model by
origin-, calendar- and development period.
Usage
# S3 method for MackChainLadder
residuals(object, ...)Arguments
- object
output of
MackChainLadder- ...
not in use
Value
The function returns a data.frame of residuals and standardised residuals
by origin-, calendar- and development period.
See also
See Also MackChainLadder
Examples
RAA
#> dev
#> origin 1 2 3 4 5 6 7 8 9 10
#> 1981 5012 8269 10907 11805 13539 16181 18009 18608 18662 18834
#> 1982 106 4285 5396 10666 13782 15599 15496 16169 16704 NA
#> 1983 3410 8992 13873 16141 18735 22214 22863 23466 NA NA
#> 1984 5655 11555 15766 21266 23425 26083 27067 NA NA NA
#> 1985 1092 9565 15836 22169 25955 26180 NA NA NA NA
#> 1986 1513 6445 11702 12935 15852 NA NA NA NA NA
#> 1987 557 4020 10946 12314 NA NA NA NA NA NA
#> 1988 1351 6947 13112 NA NA NA NA NA NA NA
#> 1989 3133 5395 NA NA NA NA NA NA NA NA
#> 1990 2063 NA NA NA NA NA NA NA NA NA
MCL=MackChainLadder(RAA)
MCL
#> MackChainLadder(Triangle = RAA)
#>
#> Latest Dev.To.Date Ultimate IBNR Mack.S.E CV(IBNR)
#> 1981 18,834 1.000 18,834 0 0 NaN
#> 1982 16,704 0.991 16,858 154 143 0.928
#> 1983 23,466 0.974 24,083 617 592 0.959
#> 1984 27,067 0.943 28,703 1,636 713 0.436
#> 1985 26,180 0.905 28,927 2,747 1,452 0.529
#> 1986 15,852 0.813 19,501 3,649 1,995 0.547
#> 1987 12,314 0.694 17,749 5,435 2,204 0.405
#> 1988 13,112 0.546 24,019 10,907 5,354 0.491
#> 1989 5,395 0.336 16,045 10,650 6,332 0.595
#> 1990 2,063 0.112 18,402 16,339 24,566 1.503
#>
#> Totals
#> Latest: 160,987.00
#> Dev: 0.76
#> Ultimate: 213,122.23
#> IBNR: 52,135.23
#> Mack.S.E 26,880.74
#> CV(IBNR): 0.52
residuals(MCL)
#> origin.period dev.period cal.period residuals standard.residuals
#> 1 1981 1 1981 -6.763786e+03 -0.6518587127
#> 2 1982 1 1982 3.967068e+03 2.3131310956
#> 3 1983 1 1983 -1.235813e+03 -0.1379704193
#> 4 1984 1 1984 -5.406373e+03 -0.5001778243
#> 5 1985 1 1985 6.289700e+03 1.1694700671
#> 6 1986 1 1986 1.906970e+03 0.3043328370
#> 7 1987 1 1987 2.349357e+03 0.6038940301
#> 8 1988 1 1988 2.894866e+03 0.4869681180
#> 9 1989 1 1989 -4.001991e+03 -0.4626632036
#> 10 1981 2 1982 -2.517910e+03 -0.8955622462
#> 11 1982 2 1983 -1.560795e+03 -0.7431309175
#> 12 1983 2 1984 -7.257166e+02 -0.2492715390
#> 13 1984 2 1985 -2.993805e+03 -0.9307852849
#> 14 1985 2 1986 3.070049e+02 0.1028219694
#> 15 1986 2 1987 1.238396e+03 0.4903618988
#> 16 1987 2 1988 4.419439e+03 2.1673048699
#> 17 1988 2 1989 1.833387e+03 0.7025323710
#> 18 1981 3 1983 -2.056577e+03 -0.8025136628
#> 19 1982 3 1984 3.808288e+03 2.0377822470
#> 20 1983 3 1985 -1.490031e+03 -0.5262744644
#> 21 1984 3 1986 1.229178e+03 0.4128212956
#> 22 1985 3 1987 2.043216e+03 0.6850481136
#> 23 1986 3 1988 -1.936933e+03 -0.7336781618
#> 24 1987 3 1989 -1.597141e+03 -0.6222874301
#> 25 1981 4 1984 -2.926190e+02 -0.3677955805
#> 26 1982 4 1985 1.284918e+03 1.6875563766
#> 27 1983 4 1986 -1.770003e+02 -0.1954209622
#> 28 1984 4 1987 -1.491833e+03 -1.4840033877
#> 29 1985 4 1988 -1.985494e+01 -0.0194638893
#> 30 1986 4 1989 6.963886e+02 0.8419293284
#> 31 1981 5 1985 1.106882e+03 0.9396302313
#> 32 1982 5 1986 2.543295e+02 0.2143062398
#> 33 1983 5 1987 1.354734e+03 1.0102053305
#> 34 1984 5 1988 1.959041e+00 0.0013483019
#> 35 1985 5 1989 -2.717905e+03 -1.8091460074
#> 36 1981 6 1986 1.149456e+03 1.5833277459
#> 37 1982 6 1987 -7.571384e+02 -1.0573998685
#> 38 1983 6 1988 -2.825360e+02 -0.3490423583
#> 39 1984 6 1989 -1.097812e+02 -0.1295670061
#> 40 1981 7 1987 -4.334019e-02 -0.0003377707
#> 41 1982 7 1988 1.575480e+02 1.2823293692
#> 42 1983 7 1989 -1.575046e+02 -1.1656855985
#> 43 1981 8 1988 -2.611540e+02 -1.0000000000
#> 44 1982 8 1989 2.611540e+02 1.0000000000
#> fitted.value
#> 1 15032.786
#> 2 317.932
#> 3 10227.813
#> 4 16961.373
#> 5 3275.300
#> 6 4538.030
#> 7 1670.643
#> 8 4052.134
#> 9 9396.991
#> 10 13424.910
#> 11 6956.795
#> 12 14598.717
#> 13 18759.805
#> 14 15528.995
#> 15 10463.604
#> 16 6526.561
#> 17 11278.613
#> 18 13861.577
#> 19 6857.712
#> 20 17631.031
#> 21 20036.822
#> 22 20125.784
#> 23 14871.933
#> 24 13911.141
#> 25 13831.619
#> 26 12497.082
#> 27 18912.000
#> 28 24916.833
#> 29 25974.855
#> 30 15155.611
#> 31 15074.118
#> 32 15344.671
#> 33 20859.266
#> 34 26081.041
#> 35 28897.905
#> 36 16859.544
#> 37 16253.138
#> 38 23145.536
#> 39 27176.781
#> 40 18608.043
#> 41 16011.452
#> 42 23623.505
#> 43 18923.154
#> 44 16442.846