a4aGrpredict-a4aGr.RdPredicts ages or lengths using a growth class
# S4 method for class 'a4aGr'
predict(object, ...)a matrix object with lengths or ages
# Set up the a4aGr object and parameters for the marginals
mm <- matrix(NA, ncol=3, nrow=3)
diag(mm) <- c(50, 0.001,0.001)
mm[upper.tri(mm)] <- mm[lower.tri(mm)] <- c(0.1,0.01,0.00004)
md <- ~linf*(1-exp(-k*(t-t0)))
imd <- ~t0-1/k*log(1-len/linf)
prs <- FLPar(linf=58.5, k=0.086, t0=0.001, units=c("cm","yr^-1","yr"))
vbObj <- a4aGr(grMod=md, grInvMod=imd, params=prs, vcov=mm, distr="norm")
predict(vbObj, len=1:50+0.5)
#> iter
#> 1
#> 1.5 0.3030405
#> 2.5 0.5088496
#> 3.5 0.7183671
#> 4.5 0.9317292
#> 5.5 1.1490795
#> 6.5 1.3705702
#> 7.5 1.5963619
#> 8.5 1.8266250
#> 9.5 2.0615402
#> 10.5 2.3012993
#> 11.5 2.5461064
#> 12.5 2.7961786
#> 13.5 3.0517473
#> 14.5 3.3130595
#> 15.5 3.5803795
#> 16.5 3.8539900
#> 17.5 4.1341940
#> 18.5 4.4213174
#> 19.5 4.7157106
#> 20.5 5.0177511
#> 21.5 5.3278470
#> 22.5 5.6464397
#> 23.5 5.9740081
#> 24.5 6.3110724
#> 25.5 6.6581999
#> 26.5 7.0160099
#> 27.5 7.3851808
#> 28.5 7.7664578
#> 29.5 8.1606619
#> 30.5 8.5687005
#> 31.5 8.9915801
#> 32.5 9.4304211
#> 33.5 9.8864759
#> 34.5 10.3611503
#> 35.5 10.8560295
#> 36.5 11.3729105
#> 37.5 11.9138409
#> 38.5 12.4811684
#> 39.5 13.0776020
#> 40.5 13.7062907
#> 41.5 14.3709234
#> 42.5 15.0758608
#> 43.5 15.8263088
#> 44.5 16.6285514
#> 45.5 17.4902721
#> 46.5 18.4210012
#> 47.5 19.4327614
#> 48.5 20.5410193
#> 49.5 21.7661416
#> 50.5 23.1357118
predict(vbObj, t=1:20+0.5)
#> iter
#> 1
#> 1.5 7.075601
#> 2.5 11.313268
#> 3.5 15.201727
#> 4.5 18.769754
#> 5.5 22.043756
#> 6.5 25.047961
#> 7.5 27.804602
#> 8.5 30.334079
#> 9.5 32.655114
#> 10.5 34.784882
#> 11.5 36.739144
#> 12.5 38.532364
#> 13.5 40.177813
#> 14.5 41.687666
#> 15.5 43.073100
#> 16.5 44.344365
#> 17.5 45.510871
#> 18.5 46.581250
#> 19.5 47.563424
#> 20.5 48.464661