I didn't use a regular loop because it is a package and the segments are not going to be "numeric" I want to run this package separately on each segment of the data. Example code of me trying and getting "NULL". The real issue is that I am automating this process and this single case is just an example.
frame<-read.delim('F:/SonoT/2019/Sampling_Frame.txt', header=T, sep="\t")
attach(frame)
names(frame)
datapre<-split(frame$Billing.Amount,frame$CustomerName)
**data<-as.double(frame$Billing.Amount)**
n_min=6
n_max=11
Ls_max=2
lapply(datapre,function(x){for (n in n_min:n_max){res<-strata.LH(**data**, n, CV = NULL, Ls, certain = NULL,
alloc = list(q1 = 0.5, q2 = 0, q3 = 0.5), takenone = 1,
bias.penalty = 1, takeall = 1, rh = rep(1, Ls),
model = c("none"),
model.control = list(), initbh = NULL,
algo = c("Kozak"), algo.control = list())}})
In Bold is where I believe the most fundamental problems are. I split the data so as.double isn't going to work so simply and I'm trying to iterate and automate so singular processes aren't super handy. I'm in search of the right solution to help me segment the data then perform this packaged function on all segments of the original frame. Thanks!!!
(Note Sampling_Frame is just 3 columns of code, one Identifier, the second used to segment, the third is numeric which will be used to stratify)
Below is an the data from the txt file "Sampling_Frame" for a minimal working example
JOB CustomerName Billing Amount
18-1938 LMT 844874.4
19-1376 PJR 537137.73
19-1352 PJR 488824.38
19-1021 PJR 470939.12
19-1798 PJR 457664.7
19-2088 PJR 297236
19-1677 PJR 289618.08
19-1375 PJR 247639.19
19-1365 PJR 219043.63
18-1823 PJR 209307.34
19-1818 PJR 200998.77
19-1817 PJR 190823.68
19-1276 PJR 181501.92
19-1815 PJR 176378.26
19-1032 LMT 148820.26
19-1084 LMT 138196.34
19-1067 LMT 136659.39
19-1741 LMT 124441.03
19-1083 LMT 123765.9
19-1831 LMT 123562.68
19-2051 LMT 123165.17
19-1514 LMT 118154.4
19-1358 PJR 116789.4
19-1489 PJR 110486.26
19-1535 LMT 107360.87
19-1495 LMT 106515.48
19-1498 LMT 106515.48
19-1497 LMT 106515.48
19-1214 LMT 105693.57
19-1380 LMT 102042.72
19-1724 LMT 99093.09
19-1392 LMT 95834.17
19-1491 RNF 95309.95
19-1626 RNF 92679.44
19-1311 RNF 92531.28
19-1541 RNF 91908
19-1023 RNF 91560.24
19-1132 RNF 90712.05
19-1476 RNF 87297.18
19-1478 RNF 87297.18
19-1341 RNF 86788.79
19-1007 RNF 85865.83
19-1043 RNF 85664.88
19-1044 RNF 85664.88
19-1182 PJR 85664.88
19-1099 PJR 83723.56
19-1085 PJR 83518.56
19-1597 PJR 79901.25
19-1183 PJR 79827.21
19-1299 RNF 79098.81
19-1371 RNF 75446.28
18-1893 RNF 75364.76
18-1938 LMT 535420.2907
19-1376 PJR 665971.1543
19-1352 PJR 113937.3254
19-1021 PJR 901412.9552
19-1798 PJR 180870.6582
19-2088 PJR 459256.6056
19-1677 PJR 786567.9076
19-1375 PJR 107233.7503
19-1365 PJR 529049.9652
18-1823 PJR 93935.11101
19-1818 PJR 781140.9755
19-1817 PJR 626540.2303
19-1276 PJR 994367.0361
19-1815 PJR 248037.5789
19-1032 LMT 591415.5152
19-1084 LMT 955234.6192
19-1067 LMT 985639.924
19-1741 LMT 41756.03667
19-1083 LMT 422216.9353
19-1831 LMT 514984.3071
19-2051 LMT 921309.5568
19-1514 LMT 836335.2603
19-1358 PJR 606062.0096
19-1489 PJR 490173.5946
19-1535 LMT 980659.3195
19-1495 LMT 302602.6893
19-1498 LMT 669464.3852
19-1497 LMT 354799.0461
19-1214 LMT 589567.4014
19-1380 LMT 210924.1892
19-1724 LMT 76164.3439
19-1392 LMT 208655.3566
19-1491 RNF 509698.2722
19-1626 RNF 622272.0624
19-1311 RNF 259806.3957
19-1541 RNF 839041.7736
19-1023 RNF 796422.9877
19-1132 RNF 106002.6997
19-1476 RNF 551992.2614
19-1478 RNF 735833.4733
19-1341 RNF 110942.0706
19-1007 RNF 586964.3845
19-1043 RNF 39630.9694
19-1044 RNF 121490.1144
19-1182 PJR 134848.2189
19-1099 PJR 869101.0679
19-1085 PJR 486720.2974
19-1597 PJR 319308.3749
19-1183 PJR 747375.1898
19-1299 RNF 408166.5797
19-1371 RNF 989657.9436
18-1893 RNF 621918.6124