CRAN Package Check Results for Package LogicForest

Last updated on 2018-04-25 15:48:15 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2.1.0 6.71 69.06 75.77 ERROR
r-devel-linux-x86_64-debian-gcc 2.1.0 5.89 53.08 58.97 ERROR
r-devel-linux-x86_64-fedora-clang 2.1.0 107.89 NOTE
r-devel-linux-x86_64-fedora-gcc 2.1.0 102.44 NOTE
r-devel-windows-ix86+x86_64 2.1.0 16.00 89.00 105.00 NOTE
r-patched-linux-x86_64 2.1.0 6.03 66.69 72.72 ERROR
r-patched-solaris-x86 2.1.0 141.40 NOTE
r-release-linux-x86_64 2.1.0 5.21 66.41 71.62 ERROR
r-release-windows-ix86+x86_64 2.1.0 16.00 89.00 105.00 NOTE
r-release-osx-x86_64 2.1.0 NOTE
r-oldrel-windows-ix86+x86_64 2.1.0 8.00 120.00 128.00 NOTE
r-oldrel-osx-x86_64 2.1.0 NOTE

Check Details

Version: 2.1.0
Check: S3 generic/method consistency
Result: NOTE
    Found the following apparent S3 methods exported but not registered:
     predict.LBoost predict.logforest print.LBoost print.LFprediction
     print.logforest
    See section ‘Registering S3 methods’ in the ‘Writing R Extensions’
    manual.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64

Version: 2.1.0
Check: R code for possible problems
Result: NOTE
    BoostVimp.plot: no visible global function definition for ‘par’
    BoostVimp.plot: no visible global function definition for ‘plot’
    BoostVimp.plot: no visible global function definition for ‘segments’
    BoostVimp.plot: no visible global function definition for ‘axis’
    BoostVimp.plot: no visible global function definition for ‘plot.new’
    TTab: no visible global function definition for ‘is’
    ada.pred: no visible global function definition for ‘predict’
    ada.weights: no visible global function definition for ‘predict’
    persistence.plot: no visible global function definition for ‘par’
    persistence.plot: no visible global function definition for ‘text’
    persistence.plot: no visible global function definition for ‘segments’
    persistence.plot: no visible global function definition for ‘legend’
    predict.LBoost: no visible global function definition for ‘predict’
    submatch.plot: no visible global function definition for ‘colors’
    submatch.plot: no visible global function definition for ‘layout’
    submatch.plot: no visible global function definition for ‘par’
    submatch.plot: no visible global function definition for ‘symbols’
    submatch.plot: no visible global function definition for ‘abline’
    submatch.plot: no visible global function definition for ‘axis’
    submatch.plot: no visible global function definition for ‘barplot’
    vimp.plot: no visible global function definition for ‘par’
    vimp.plot: no visible global function definition for ‘plot’
    vimp.plot: no visible global function definition for ‘segments’
    vimp.plot: no visible global function definition for ‘axis’
    Undefined global functions or variables:
     abline axis barplot colors is layout legend par plot plot.new predict
     segments symbols text
    Consider adding
     importFrom("grDevices", "colors")
     importFrom("graphics", "abline", "axis", "barplot", "layout", "legend",
     "par", "plot", "plot.new", "segments", "symbols", "text")
     importFrom("methods", "is")
     importFrom("stats", "predict")
    to your NAMESPACE file (and ensure that your DESCRIPTION Imports field
    contains 'methods').
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64

Version: 2.1.0
Check: examples
Result: ERROR
    Running examples in ‘LogicForest-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: logforest
    > ### Title: Logic Forest
    > ### Aliases: logforest
    >
    > ### ** Examples
    >
    > data(LF.data)
    >
    > #Set using annealing parameters using the logreg.anneal.control
    > #function from LogicReg package
    >
    > newanneal<-logreg.anneal.control(start=1, end=-2, iter=2500)
    >
    > #typically more than 2500 iterations (iter>25000) would be used for
    > #the annealing algorithm. A typical forest also contains at
    > #least 100 trees. These parameters were set to allow for faster
    > #run times
    >
    > #The data set LF.data contains 50 binary predictors and a binary
    > #response Ybin
    > LF.fit1<-logforest(resp=LF.data$Ybin, Xs=LF.data[,1:50], nBS=20,
    + anneal.params=newanneal)
    > print(LF.fit1)
    $AllFits
    $AllFits[[1]]
    score 28
     +1 * (X5 and X4)
    
    $AllFits[[2]]
    score 15
     +1 * (X4 and X5)
    
    $AllFits[[3]]
    score 33
     +1 * X5
    
    $AllFits[[4]]
    score 16
     +1 * ((X5 and X4) or ((X43 and X44) and ((not X26) and (not X47))))
    
    $AllFits[[5]]
    score 23
     +1 * (X4 or (((not X48) and (not X2)) and (X50 and X1)))
    
    $AllFits[[6]]
    score 10
     +1 * ((X5 and X4) or (X10 and X9))
    
    $AllFits[[7]]
    score 33
     +1 * (X5 and X4)
    
    $AllFits[[8]]
    score 15
     +1 * (X5 and X4)
    
    $AllFits[[9]]
    score 27
     +1 * ((((not X37) or (not X49)) or ((not X15) and X5)) and X4)
    
    $AllFits[[10]]
    score 13
     +1 * (X5 and X4)
    
    $AllFits[[11]]
    score 30
     +1 * (X5 and X4)
    
    $AllFits[[12]]
    score 26
     +1 * (X5 and X4)
    
    $AllFits[[13]]
    score 16
     +1 * (X4 and X5)
    
    $AllFits[[14]]
    score 28
     +1 * (X5 and X4)
    
    $AllFits[[15]]
    score 16
     +1 * (X5 and X4)
    
    $AllFits[[16]]
    score 23
     +1 * (X4 and X5)
    
    $AllFits[[17]]
    score 22
     +1 * (X4 and X5)
    
    $AllFits[[18]]
    score 24
     +1 * (X5 and X4)
    
    $AllFits[[19]]
    score 23
     +1 * (X5 and X4)
    
    $AllFits[[20]]
    score 22
     +1 * (X5 and ((not X9) or X4))
    
    
    $Top5.PI
    [1] "X4 & X5" "X4" "X5" "X5 & !X9"
    [5] "X4 & X5 & !X15"
    
    $Predictor.importance
     X1 X2 X3 X4 X5 X6
    -0.01408451 0.00000000 0.00000000 3.94811604 4.12274765 0.00000000
     X7 X8 X9 X10 X11 X12
     0.00000000 0.00000000 0.05524642 0.16216216 0.00000000 0.00000000
     X13 X14 X15 X16 X17 X18
     0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
     X19 X20 X21 X22 X23 X24
     0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
     X25 X26 X27 X28 X29 X30
     0.00000000 0.02702703 0.00000000 0.00000000 0.00000000 0.00000000
     X31 X32 X33 X34 X35 X36
     0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
     X37 X38 X39 X40 X41 X42
     0.05479452 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
     X43 X44 X45 X46 X47 X48
     0.02702703 0.04054054 0.00000000 0.00000000 0.00000000 -0.01408451
     X49 X50
     0.00000000 0.05633803
    
    $Predictor.frequency
    
     X1 X10 X15 X2 X26 X37 X4 X43 X44 X47 X48 X49 X5 X50 X9
     1 1 1 1 1 1 19 1 1 1 1 1 19 1 2
    
    $PI.frequency
    
    !X26 & X43 & X44 & !X47 X1 & !X2 & !X48 & X50 X4
     1 1 1
     X4 & !X37 X4 & !X49 X4 & X5
     1 1 17
     X4 & X5 & !X15 X5 X5 & !X9
     1 1 1
     X9 & X10
     1
    
    $PI.importance
     X4 & X5 X5 !X26 & X43 & X44 & !X47
     6.08645202 0.34666667 0.02702703
     X4 X1 & !X2 & !X48 & X50 X9 & X10
     0.35211268 0.05633803 0.01351351
     X4 & !X37 X4 & !X49 X4 & X5 & !X15
     0.05479452 0.09589041 0.12328767
     X5 & !X9
     0.16176471
    
    $ModelPI.import
    $ModelPI.import[[1]]
     X4 & X5
    0.4102564
    
    $ModelPI.import[[2]]
     X4 & X5
    0.2933333
    
    $ModelPI.import[[3]]
     X5
    0.3466667
    
    $ModelPI.import[[4]]
     X4 & X5 !X26 & X43 & X44 & !X47
     0.47297297 0.02702703
    
    $ModelPI.import[[5]]
     X4 X1 & !X2 & !X48 & X50
     0.35211268 0.05633803
    
    $ModelPI.import[[6]]
     X4 & X5 X9 & X10
    0.36486486 0.01351351
    
    $ModelPI.import[[7]]
     X4 & X5
    0.4117647
    
    $ModelPI.import[[8]]
     X4 & X5
    0.3823529
    
    $ModelPI.import[[9]]
     X4 & !X37 X4 & !X49 X4 & X5 & !X15
     0.05479452 0.09589041 0.12328767
    
    $ModelPI.import[[10]]
    X4 & X5
     0.225
    
    $ModelPI.import[[11]]
     X4 & X5
    0.358209
    
    $ModelPI.import[[12]]
     X4 & X5
    0.3783784
    
    $ModelPI.import[[13]]
     X4 & X5
    0.3466667
    
    $ModelPI.import[[14]]
     X4 & X5
    0.3013699
    
    $ModelPI.import[[15]]
     X4 & X5
    0.4266667
    
    $ModelPI.import[[16]]
     X4 & X5
    0.4415584
    
    $ModelPI.import[[17]]
     X4 & X5
    0.3823529
    
    $ModelPI.import[[18]]
     X4 & X5
    0.2894737
    
    $ModelPI.import[[19]]
     X4 & X5
    0.3953488
    
    $ModelPI.import[[20]]
     X4 & X5 X5 & !X9
    0.2058824 0.1617647
    
    
    $OOBmisclass
    [1] 0.115
    
    $OOBprediction
     predicted_class proportion
     [1,] 1 1.00000000
     [2,] 1 1.00000000
     [3,] 0 0.00000000
     [4,] 0 0.00000000
     [5,] 0 0.00000000
     [6,] 1 1.00000000
     [7,] 0 0.00000000
     [8,] 0 0.00000000
     [9,] 0 0.00000000
     [10,] 0 0.00000000
     [11,] 0 0.00000000
     [12,] 1 1.00000000
     [13,] 1 1.00000000
     [14,] 0 0.00000000
     [15,] 0 0.33333333
     [16,] 1 1.00000000
     [17,] 0 0.00000000
     [18,] 1 1.00000000
     [19,] 0 0.00000000
     [20,] 1 1.00000000
     [21,] 0 0.20000000
     [22,] 0 0.00000000
     [23,] 0 0.00000000
     [24,] 0 0.00000000
     [25,] 0 0.00000000
     [26,] 1 1.00000000
     [27,] 1 1.00000000
     [28,] 1 1.00000000
     [29,] 1 1.00000000
     [30,] 0 0.00000000
     [31,] 0 0.00000000
     [32,] 0 0.00000000
     [33,] 1 1.00000000
     [34,] 0 0.00000000
     [35,] 0 0.00000000
     [36,] 1 1.00000000
     [37,] 0 0.00000000
     [38,] 0 0.00000000
     [39,] 0 0.00000000
     [40,] 0 0.00000000
     [41,] 0 0.00000000
     [42,] 0 0.00000000
     [43,] 0 0.14285714
     [44,] 1 0.85714286
     [45,] 0 0.00000000
     [46,] 0 0.00000000
     [47,] 1 1.00000000
     [48,] 0 0.00000000
     [49,] 1 1.00000000
     [50,] 1 1.00000000
     [51,] 1 1.00000000
     [52,] 1 1.00000000
     [53,] 0 0.00000000
     [54,] 1 1.00000000
     [55,] 0 0.00000000
     [56,] 1 1.00000000
     [57,] 0 0.20000000
     [58,] 1 1.00000000
     [59,] 1 1.00000000
     [60,] 0 0.00000000
     [61,] 1 1.00000000
     [62,] 0 0.08333333
     [63,] 1 1.00000000
     [64,] 0 0.00000000
     [65,] 1 1.00000000
     [66,] 0 0.25000000
     [67,] 1 1.00000000
     [68,] 1 1.00000000
     [69,] 1 1.00000000
     [70,] 1 1.00000000
     [71,] 1 1.00000000
     [72,] 1 1.00000000
     [73,] 1 1.00000000
     [74,] 0 0.00000000
     [75,] 1 1.00000000
     [76,] 0 0.00000000
     [77,] 0 0.00000000
     [78,] 1 1.00000000
     [79,] 0 0.00000000
     [80,] 0 0.00000000
     [81,] 1 1.00000000
     [82,] 1 1.00000000
     [83,] 0 0.00000000
     [84,] 1 1.00000000
     [85,] 1 1.00000000
     [86,] 1 1.00000000
     [87,] 1 1.00000000
     [88,] 1 1.00000000
     [89,] 1 1.00000000
     [90,] 1 1.00000000
     [91,] 1 1.00000000
     [92,] 0 0.00000000
     [93,] 1 1.00000000
     [94,] 1 1.00000000
     [95,] 1 1.00000000
     [96,] 1 1.00000000
     [97,] 0 0.00000000
     [98,] 1 1.00000000
     [99,] 0 0.00000000
    [100,] 0 0.00000000
    [101,] 0 0.12500000
    [102,] 0 0.00000000
    [103,] 0 0.00000000
    [104,] 0 0.00000000
    [105,] 1 1.00000000
    [106,] 0 0.00000000
    [107,] 1 1.00000000
    [108,] 1 1.00000000
    [109,] 0 0.00000000
    [110,] 0 0.00000000
    [111,] 0 0.00000000
    [112,] 0 0.00000000
    [113,] 0 0.00000000
    [114,] 0 0.00000000
    [115,] 0 0.00000000
    [116,] 1 1.00000000
    [117,] 0 0.00000000
    [118,] 0 0.00000000
    [119,] 0 0.00000000
    [120,] 0 0.00000000
    [121,] 0 0.14285714
    [122,] 1 1.00000000
    [123,] 0 0.00000000
    [124,] 1 1.00000000
    [125,] 0 0.00000000
    [126,] 1 1.00000000
    [127,] 1 1.00000000
    [128,] 1 1.00000000
    [129,] 0 0.00000000
    [130,] 0 0.00000000
    [131,] 0 0.00000000
    [132,] 0 0.00000000
    [133,] 0 0.22222222
    [134,] 1 1.00000000
    [135,] 1 1.00000000
    [136,] 1 1.00000000
    [137,] 0 0.00000000
    [138,] 1 1.00000000
    [139,] 1 1.00000000
    [140,] 1 1.00000000
    [141,] 0 0.00000000
    [142,] 0 0.09090909
    [143,] 1 0.80000000
    [144,] 1 0.88888889
    [145,] 1 1.00000000
    [146,] 1 1.00000000
    [147,] 0 0.00000000
    [148,] 0 0.00000000
    [149,] 1 1.00000000
    [150,] 0 0.00000000
    [151,] 1 1.00000000
    [152,] 0 0.00000000
    [153,] 1 1.00000000
    [154,] 1 1.00000000
    [155,] 1 1.00000000
    [156,] 0 0.14285714
    [157,] 0 0.00000000
    [158,] 0 0.00000000
    [159,] 1 1.00000000
    [160,] 0 0.00000000
    [161,] 1 1.00000000
    [162,] 0 0.00000000
    [163,] 0 0.00000000
    [164,] 0 0.11111111
    [165,] 0 0.14285714
    [166,] 0 0.00000000
    [167,] 0 0.08333333
    [168,] 1 1.00000000
    [169,] 1 1.00000000
    [170,] 1 1.00000000
    [171,] 0 0.00000000
    [172,] 0 0.00000000
    [173,] 0 0.00000000
    [174,] 0 0.00000000
    [175,] 0 0.00000000
    [176,] 0 0.11111111
    [177,] 1 1.00000000
    [178,] 0 0.12500000
    [179,] 0 0.00000000
    [180,] 0 0.16666667
    [181,] 0 0.00000000
    [182,] 1 1.00000000
    [183,] 0 0.00000000
    [184,] 1 1.00000000
    [185,] 0 0.00000000
    [186,] 0 0.00000000
    [187,] 0 0.00000000
    [188,] 0 0.00000000
    [189,] 1 1.00000000
    [190,] 1 1.00000000
    [191,] 1 1.00000000
    [192,] 0 0.00000000
    [193,] 1 1.00000000
    [194,] 1 1.00000000
    [195,] 0 0.00000000
    [196,] 0 0.00000000
    [197,] 1 1.00000000
    [198,] 1 1.00000000
    [199,] 0 0.11111111
    [200,] 0 0.00000000
    
    $IBdata
    $IBdata[[1]]
     [1] 75 115 182 41 180 189 133 126 13 42 36 138 77 154 100 144 199 77
     [19] 156 187 43 131 26 54 78 3 77 174 69 97 120 99 38 166 134 159
     [37] 22 145 83 165 130 157 111 106 158 5 96 147 139 96 173 88 49 15
     [55] 20 64 104 133 82 183 59 92 67 131 52 96 154 17 176 68 168 70
     [73] 67 96 179 173 78 156 193 87 143 80 66 152 41 143 25 50 29 48
     [91] 12 129 176 156 160 92 83 163 121 131 71 55 199 127 43 26 96 185
    [109] 120 196 147 72 87 30 3 144 21 90 129 199 100 97 35 151 91 103
    [127] 42 46 120 115 16 8 129 186 120 113 106 198 102 137 121 48 52 146
    [145] 91 36 150 21 173 123 112 66 91 101 37 106 16 56 43 57 180 90
    [163] 156 177 83 13 68 145 68 127 169 172 79 77 180 129 149 122 181 59
    [181] 39 178 101 176 38 152 145 189 110 143 78 21 186 57 119 23 169 64
    [199] 157 54
    
    $IBdata[[2]]
     [1] 86 3 184 16 102 165 120 85 112 158 34 195 95 186 181 151 136 130
     [19] 15 85 107 189 143 145 95 25 157 88 87 6 30 85 154 1 121 182
     [37] 142 53 171 67 116 87 11 146 110 151 11 143 60 57 166 18 9 70
     [55] 109 122 55 42 77 95 168 25 136 100 181 111 26 89 39 87 46 193
     [73] 90 156 32 174 42 36 33 114 146 176 142 96 165 4 200 127 86 6
     [91] 151 42 200 182 143 147 95 173 34 125 59 92 10 36 12 189 69 104
    [109] 126 48 104 162 70 172 7 195 150 55 136 70 190 68 7 71 78 72
    [127] 192 77 110 186 184 49 144 70 111 149 164 174 8 45 74 62 146 140
    [145] 183 170 156 81 116 16 175 192 102 185 27 48 98 95 87 8 129 144
    [163] 71 190 149 11 197 44 8 53 145 50 47 5 53 139 7 13 80 99
    [181] 127 145 16 85 195 163 45 98 3 52 91 149 199 67 189 193 180 99
    [199] 157 161
    
    $IBdata[[3]]
     [1] 118 63 112 71 29 114 67 25 52 71 167 157 189 168 30 119 165 127
     [19] 94 52 5 66 45 176 136 106 112 50 2 190 144 56 149 175 77 144
     [37] 48 130 196 76 93 163 99 11 27 33 18 81 13 113 68 109 183 78
     [55] 193 77 189 137 181 51 82 3 23 101 75 162 2 168 76 78 191 96
     [73] 111 187 173 52 138 90 44 138 192 52 94 65 33 143 106 47 13 136
     [91] 162 24 139 5 73 147 63 90 166 67 29 61 33 168 133 28 66 167
    [109] 165 30 85 90 177 83 138 144 3 8 19 80 181 89 152 143 34 174
    [127] 18 33 170 126 42 135 193 177 193 93 15 175 40 107 22 77 150 140
    [145] 20 123 5 130 196 169 169 78 159 82 51 84 100 172 147 195 21 167
    [163] 91 171 114 193 191 57 148 15 181 27 112 121 27 102 74 1 10 177
    [181] 165 83 185 96 95 132 33 20 173 48 112 170 70 196 174 151 45 154
    [199] 175 9
    
    $IBdata[[4]]
     [1] 155 53 136 199 111 187 42 46 97 93 157 1 151 167 63 143 51 62
     [19] 140 85 171 107 110 170 76 34 38 172 68 156 14 49 49 78 175 194
     [37] 174 88 39 17 117 15 106 95 10 119 159 120 6 80 22 5 169 66
     [55] 59 165 83 3 11 147 15 15 128 83 87 17 56 159 19 56 28 133
     [73] 196 43 75 24 157 14 157 25 156 73 124 184 22 144 32 53 155 119
     [91] 20 32 141 54 60 113 70 200 43 119 82 108 162 3 135 177 82 179
    [109] 162 11 191 100 100 41 137 110 122 62 33 170 36 118 195 107 163 131
    [127] 155 7 112 25 138 183 113 116 104 132 118 16 32 198 199 59 158 138
    [145] 81 80 178 165 54 37 192 168 70 169 3 43 183 10 175 132 44 2
    [163] 16 154 7 155 79 157 7 74 42 194 113 89 161 34 42 70 91 21
    [181] 121 21 192 117 34 104 11 37 7 83 143 88 96 76 156 193 89 56
    [199] 131 151
    
    $IBdata[[5]]
     [1] 86 28 163 162 182 141 92 17 147 187 8 22 80 31 23 58 117 29
     [19] 99 73 82 57 86 93 166 72 88 2 194 68 6 72 129 58 197 17
     [37] 26 53 43 190 70 82 108 56 82 88 65 1 195 23 110 175 173 123
     [55] 1 65 175 102 182 198 63 3 83 155 191 146 104 147 171 164 145 89
     [73] 88 168 78 135 16 166 4 23 99 137 122 180 62 109 148 32 137 177
     [91] 74 7 104 23 181 44 125 73 158 191 138 3 192 100 109 12 33 152
    [109] 65 124 119 10 79 63 87 72 150 191 44 166 6 190 196 163 134 60
    [127] 171 170 76 174 108 116 4 183 128 111 137 188 37 89 60 91 183 155
    [145] 137 126 81 11 129 44 18 27 176 131 6 27 32 95 151 169 176 3
    [163] 9 43 146 159 127 30 98 150 54 152 40 76 113 91 178 118 14 27
    [181] 30 173 190 180 23 159 1 140 102 54 127 200 102 187 39 97 127 41
    [199] 86 135
    
    $IBdata[[6]]
     [1] 157 31 3 17 104 14 163 16 31 14 88 151 3 82 83 196 45 148
     [19] 165 191 20 139 57 161 167 136 84 69 60 165 101 100 73 170 63 43
     [37] 118 169 26 76 135 38 101 6 100 190 77 140 138 96 55 152 50 105
     [55] 123 20 114 4 40 84 42 76 16 29 111 133 148 76 174 160 165 181
     [73] 197 54 158 39 1 112 82 185 105 9 114 41 87 48 198 130 157 199
     [91] 164 65 20 67 4 9 156 30 8 156 4 46 171 63 154 73 39 96
    [109] 50 190 42 179 193 196 14 7 89 65 145 171 98 77 84 125 85 52
    [127] 192 7 52 23 49 195 171 80 97 193 192 162 132 152 143 190 197 12
    [145] 50 55 182 76 56 36 95 80 27 4 125 16 132 146 15 120 19 181
    [163] 149 74 87 71 5 68 75 34 133 120 28 24 104 138 53 86 184 157
    [181] 117 179 145 68 200 67 173 97 82 52 65 190 133 95 68 162 176 130
    [199] 158 185
    
    $IBdata[[7]]
     [1] 91 69 68 160 21 58 107 22 109 74 196 101 18 120 49 135 1 81
     [19] 182 94 128 174 158 189 191 41 156 138 157 102 75 182 171 165 40 172
     [37] 105 77 188 171 173 153 1 21 85 36 161 184 55 65 117 182 148 150
     [55] 129 29 98 59 31 20 124 116 33 1 46 178 161 123 159 159 108 83
     [73] 151 185 100 116 44 33 177 94 4 164 9 15 96 95 57 43 124 13
     [91] 57 197 187 114 21 140 94 110 189 12 64 106 10 183 194 184 118 61
    [109] 85 188 39 187 65 159 175 191 71 169 171 141 75 6 180 151 74 107
    [127] 183 41 52 89 150 32 146 178 145 87 156 19 4 112 92 20 85 19
    [145] 60 8 72 50 176 64 65 170 77 56 184 176 66 19 40 36 98 29
    [163] 113 15 185 56 7 91 105 48 177 101 76 168 156 166 63 9 156 124
    [181] 42 26 193 87 128 103 134 51 20 42 92 110 179 106 135 9 70 35
    [199] 105 181
    
    $IBdata[[8]]
     [1] 31 146 95 24 53 182 157 130 105 190 94 93 192 12 138 17 65 181
     [19] 113 55 170 33 175 124 135 80 110 29 170 2 104 66 161 128 159 73
     [37] 50 89 17 66 150 119 167 152 70 182 85 12 135 118 151 81 164 171
     [55] 137 198 127 100 166 134 155 171 124 188 118 177 184 4 200 25 109 77
     [73] 95 195 26 112 56 108 137 108 59 145 199 180 62 169 67 2 79 4
     [91] 40 94 187 156 12 12 143 153 182 30 15 121 174 100 50 24 54 192
    [109] 82 153 20 200 79 153 61 75 63 90 103 59 185 20 141 3 196 101
    [127] 90 188 84 131 142 76 85 158 10 115 23 145 190 140 184 87 156 171
    [145] 153 126 36 12 181 147 132 196 27 124 80 196 37 137 31 142 31 82
    [163] 77 4 8 26 149 86 138 28 30 12 180 97 111 55 118 199 144 109
    [181] 125 135 122 138 78 105 117 149 152 141 136 156 39 168 163 171 88 105
    [199] 35 21
    
    $IBdata[[9]]
     [1] 161 145 53 183 20 41 27 169 150 165 135 89 54 21 136 80 116 191
     [19] 71 153 178 145 171 1 61 102 79 147 42 26 25 64 110 125 82 114
     [37] 31 167 42 90 150 97 69 173 200 105 130 20 11 38 80 157 16 156
     [55] 38 152 129 142 175 175 25 67 194 184 5 19 154 156 196 70 159 153
     [73] 187 91 45 64 3 104 19 125 134 100 52 85 174 38 96 177 160 104
     [91] 113 121 113 182 172 192 57 188 121 75 111 150 119 190 20 19 59 18
    [109] 67 110 54 56 65 198 168 179 154 1 104 10 104 161 99 131 139 197
    [127] 49 117 132 194 105 5 153 29 183 114 168 63 177 43 158 24 106 59
    [145] 7 12 199 51 111 164 98 45 21 165 121 126 69 131 54 4 62 6
    [163] 114 112 53 193 157 166 96 91 49 180 177 90 128 100 198 188 106 24
    [181] 57 89 140 39 138 59 16 11 106 110 116 168 18 94 18 77 80 147
    [199] 156 183
    
    $IBdata[[10]]
     [1] 171 10 195 187 195 152 156 34 39 24 98 100 59 152 50 81 71 100
     [19] 193 112 117 141 195 24 108 199 92 19 6 18 113 82 88 93 29 116
     [37] 140 80 199 92 18 84 69 156 50 88 72 81 58 10 28 8 149 70
     [55] 60 35 143 8 96 8 50 154 108 109 171 131 10 11 196 52 9 93
     [73] 68 50 111 112 102 60 9 185 21 141 79 72 131 133 65 69 174 172
     [91] 153 171 11 72 38 81 143 200 115 107 115 33 92 127 186 104 64 2
    [109] 194 126 135 174 123 70 26 180 74 111 199 172 64 98 84 108 16 61
    [127] 55 164 18 70 171 197 180 67 122 53 104 44 21 109 194 162 87 185
    [145] 48 152 142 3 194 153 120 188 33 125 79 1 196 134 7 54 118 98
    [163] 178 37 138 61 97 112 140 18 172 113 91 59 111 133 198 22 192 174
    [181] 80 105 172 1 36 35 116 84 127 128 175 145 184 189 130 54 193 162
    [199] 129 14
    
    $IBdata[[11]]
     [1] 73 143 172 115 83 186 115 130 166 70 173 64 14 88 52 86 185 115
     [19] 70 160 95 131 95 154 93 79 127 96 19 161 157 23 44 171 56 199
     [37] 59 69 156 168 106 167 111 108 146 52 131 18 60 135 123 101 100 31
     [55] 117 11 17 39 102 162 109 32 118 90 77 144 161 2 187 123 52 104
     [73] 19 7 159 43 63 63 121 50 110 59 91 92 137 160 16 90 141 56
     [91] 39 150 22 169 149 89 74 162 84 99 111 80 189 37 158 26 26 156
    [109] 85 144 31 18 42 5 120 145 108 16 20 190 78 194 145 183 166 21
    [127] 21 17 85 99 117 113 127 90 177 94 11 57 176 191 20 57 197 124
    [145] 8 70 103 43 75 52 178 7 78 93 51 111 130 133 177 182 71 10
    [163] 34 58 57 11 131 123 131 198 68 162 112 72 102 181 182 88 192 125
    [181] 87 95 110 115 108 157 56 21 53 196 42 73 136 132 2 197 170 95
    [199] 98 55
    
    $IBdata[[12]]
     [1] 44 5 155 25 27 87 135 171 154 83 49 142 124 81 149 188 58 8
     [19] 118 35 25 85 126 156 36 48 108 4 72 46 38 187 193 88 117 153
     [37] 187 22 87 156 40 41 66 191 107 101 198 73 78 195 177 199 69 93
     [55] 169 175 34 53 156 88 107 16 34 142 169 129 83 80 39 11 15 74
     [73] 197 154 189 41 99 192 192 37 127 192 30 86 138 165 74 182 165 75
     [91] 73 82 177 123 164 160 81 57 150 52 7 165 53 151 140 197 41 160
    [109] 2 133 76 27 78 108 55 149 9 18 134 15 172 103 134 171 148 191
    [127] 177 174 116 176 162 148 98 100 16 122 88 58 90 101 198 174 51 74
    [145] 148 51 79 36 48 165 85 141 182 143 102 172 27 78 161 117 125 80
    [163] 127 189 121 196 126 187 77 155 140 184 25 174 180 82 66 190 110 90
    [181] 183 111 29 191 104 181 144 69 145 173 73 61 31 51 147 40 36 90
    [199] 100 55
    
    $IBdata[[13]]
     [1] 189 166 77 65 182 12 23 181 40 168 126 116 15 57 178 33 87 152
     [19] 75 36 136 69 68 190 143 103 135 72 145 31 151 17 33 197 188 14
     [37] 107 12 76 34 112 149 12 87 81 171 61 186 199 121 192 127 131 195
     [55] 70 151 156 58 90 113 128 143 22 74 199 87 186 15 116 142 97 24
     [73] 39 8 99 68 89 148 104 77 137 116 141 30 196 69 129 22 122 36
     [91] 68 101 115 188 33 114 56 118 165 98 62 12 105 97 72 56 110 183
    [109] 52 4 166 10 120 197 114 146 31 64 140 171 76 56 198 27 196 129
    [127] 121 33 29 153 157 44 143 59 55 181 187 91 66 80 34 42 166 70
    [145] 120 91 19 180 53 143 50 180 35 94 160 69 96 53 198 88 147 137
    [163] 182 153 171 51 91 157 119 198 186 178 114 184 59 52 145 33 97 197
    [181] 143 121 152 9 179 154 95 180 82 154 189 154 131 185 55 193 89 53
    [199] 73 181
    
    $IBdata[[14]]
     [1] 26 14 56 121 55 189 160 18 79 35 92 97 29 7 41 53 149 71
     [19] 176 28 115 83 46 160 80 119 182 77 75 75 37 9 53 61 36 112
     [37] 75 129 185 52 48 170 140 177 42 106 46 21 21 31 24 126 104 135
     [55] 173 128 115 179 56 99 190 29 35 178 102 39 113 110 179 141 113 90
     [73] 22 132 34 98 34 26 84 52 139 50 192 153 169 176 2 8 58 17
     [91] 194 113 197 168 177 49 147 100 101 114 131 13 136 148 23 10 27 177
    [109] 168 174 7 22 110 22 145 146 158 124 101 92 7 42 69 110 154 86
    [127] 138 105 160 181 87 67 184 42 163 61 115 78 56 53 192 127 17 186
    [145] 179 183 144 137 112 81 173 15 57 33 153 24 34 96 2 195 23 17
    [163] 65 24 198 81 49 71 31 58 52 32 6 163 116 116 141 13 101 77
    [181] 86 109 129 159 170 15 173 192 186 11 50 98 21 40 43 42 6 47
    [199] 22 56
    
    $IBdata[[15]]
     [1] 119 152 14 187 127 128 26 166 60 117 61 109 165 47 192 44 155 18
     [19] 72 170 82 23 164 82 83 137 70 154 26 24 15 182 151 28 104 34
     [37] 107 1 91 144 154 46 161 82 23 44 92 122 50 182 138 69 179 127
     [55] 181 47 18 44 98 160 27 190 170 94 132 127 59 105 184 196 21 78
     [73] 165 140 49 173 192 76 165 15 30 117 100 132 151 109 127 55 165 132
     [91] 41 159 127 119 102 150 65 99 198 18 41 175 108 106 88 104 138 3
    [109] 8 33 155 120 66 29 110 48 160 47 80 15 46 129 180 160 39 143
    [127] 158 96 70 29 179 70 61 22 115 116 42 92 14 128 162 89 168 112
    [145] 139 55 190 1 61 79 109 135 5 72 29 116 6 151 102 158 189 10
    [163] 84 138 98 129 97 45 47 47 123 69 185 161 134 16 188 73 9 152
    [181] 116 142 106 74 191 129 163 124 124 198 46 74 171 160 118 159 55 100
    [199] 25 109
    
    $IBdata[[16]]
     [1] 130 170 73 114 21 11 10 81 19 62 119 98 151 81 141 70 72 196
     [19] 56 161 38 190 78 70 31 2 118 145 200 46 87 192 145 1 37 135
     [37] 24 183 71 140 200 18 142 92 182 116 138 196 105 108 93 87 35 66
     [55] 121 109 183 107 106 188 121 135 81 56 99 57 161 181 145 20 177 81
     [73] 170 143 162 121 152 3 138 143 174 74 19 190 66 189 98 197 8 53
     [91] 52 91 136 11 102 86 83 45 182 5 94 53 12 54 68 68 10 156
    [109] 108 119 45 121 74 97 195 131 97 153 197 196 103 125 143 121 55 95
    [127] 51 16 189 119 181 34 18 171 23 27 152 33 30 162 183 164 133 187
    [145] 186 193 109 120 176 134 62 145 56 74 49 45 182 103 76 84 175 42
    [163] 158 182 173 6 21 90 190 56 86 54 49 115 54 36 182 186 43 19
    [181] 65 180 131 156 162 195 89 173 6 177 187 195 74 59 57 84 44 143
    [199] 40 135
    
    $IBdata[[17]]
     [1] 141 197 92 187 175 28 185 183 84 71 183 126 35 51 49 43 191 75
     [19] 65 169 57 53 172 11 192 182 166 73 2 79 167 18 138 120 140 1
     [37] 142 112 12 164 98 115 163 97 24 168 9 173 81 150 93 80 63 26
     [55] 66 160 82 55 128 192 24 4 75 173 139 29 87 104 121 68 54 21
     [73] 27 160 3 142 98 194 80 135 141 46 58 6 190 183 143 154 115 184
     [91] 30 112 72 178 17 181 60 180 122 165 182 177 87 64 186 43 191 35
    [109] 169 112 105 16 168 42 10 93 112 107 51 94 15 50 160 28 121 174
    [127] 50 25 99 136 40 137 7 93 155 64 73 143 17 104 44 55 147 95
    [145] 79 54 190 76 89 177 187 89 133 38 47 125 11 153 61 134 177 65
    [163] 117 67 84 69 27 94 194 66 49 57 163 180 159 182 128 146 183 72
    [181] 53 195 184 190 179 148 124 168 200 160 109 76 77 4 122 68 14 19
    [199] 24 89
    
    $IBdata[[18]]
     [1] 192 90 161 45 176 146 60 193 9 146 172 15 143 183 105 92 143 127
     [19] 141 62 35 198 136 172 174 41 123 153 199 159 178 122 110 52 9 198
     [37] 12 9 134 186 95 122 125 145 178 21 22 43 125 141 172 87 76 71
     [55] 174 123 4 195 58 34 175 125 50 39 133 116 183 54 8 192 133 132
     [73] 4 100 6 167 50 102 39 113 78 129 62 158 163 68 135 146 161 54
     [91] 37 64 139 48 153 125 85 152 182 191 96 22 155 50 54 146 145 101
    [109] 65 107 117 125 24 107 185 199 26 28 161 14 190 110 159 170 60 120
    [127] 93 93 49 140 74 98 27 88 89 61 42 33 43 29 195 60 132 150
    [145] 139 158 64 184 8 67 57 73 97 128 41 53 49 145 176 101 116 93
    [163] 98 184 200 176 19 9 99 135 25 68 75 20 59 190 170 12 118 117
    [181] 99 1 67 106 16 82 59 154 67 112 185 170 63 37 117 85 199 28
    [199] 49 56
    
    $IBdata[[19]]
     [1] 173 178 172 97 115 42 139 184 30 137 190 2 106 90 196 84 197 76
     [19] 66 168 148 102 105 131 135 147 165 194 23 48 163 105 168 162 78 86
     [37] 185 82 81 108 191 33 125 128 7 35 174 189 136 187 41 47 133 95
     [55] 52 140 100 162 43 141 139 67 89 129 98 160 88 20 182 124 101 175
     [73] 122 2 155 144 170 120 63 183 46 171 170 124 108 135 189 172 49 54
     [91] 45 83 89 75 68 42 187 129 19 106 26 174 124 9 148 46 30 39
    [109] 111 196 185 134 158 78 9 21 197 155 43 183 120 46 141 66 138 196
    [127] 125 161 193 101 44 152 163 192 162 81 120 137 48 135 145 163 191 19
    [145] 96 55 166 103 175 161 5 19 42 173 153 37 69 174 9 50 155 46
    [163] 44 137 175 35 42 105 78 96 152 7 139 22 70 59 146 34 82 47
    [181] 166 96 100 39 124 180 89 4 52 172 103 171 172 23 78 175 197 5
    [199] 70 26
    
    $IBdata[[20]]
     [1] 84 195 13 198 70 60 118 98 144 186 58 26 166 122 110 144 151 12
     [19] 99 162 145 112 23 145 19 90 166 163 162 78 172 143 73 47 90 116
     [37] 156 154 63 140 174 121 186 55 148 67 194 95 75 129 185 146 6 31
     [55] 120 7 96 157 13 190 106 186 151 175 116 180 119 83 17 85 125 8
     [73] 161 185 77 66 1 83 110 114 2 187 42 16 40 101 175 59 152 52
     [91] 160 10 73 170 116 113 129 120 27 146 165 119 81 195 143 46 140 81
    [109] 51 41 71 54 43 160 54 54 10 110 158 94 84 60 12 97 190 48
    [127] 43 87 182 50 181 33 80 79 131 151 24 72 141 162 188 115 162 21
    [145] 57 93 26 100 120 35 37 112 21 179 54 21 2 17 159 112 130 42
    [163] 177 93 7 168 100 120 132 138 97 175 61 89 187 161 181 140 171 159
    [181] 123 126 31 147 87 179 116 114 49 69 16 195 9 88 150 100 109 15
    [199] 71 129
    
    
    $OOBdata
    $OOBdata[[1]]
     [1] 1 2 4 6 7 9 10 11 14 18 19 24 27 28 31 32 33 34 40
    [20] 44 45 47 51 53 58 60 61 62 63 65 73 74 76 81 84 85 86 89
    [39] 93 94 95 98 105 107 108 109 114 116 117 118 124 125 128 132 135 136 140
    [58] 141 142 148 153 155 161 162 164 167 170 171 175 184 188 190 191 192 194 195
    [77] 197 200
    
    $OOBdata[[2]]
     [1] 2 14 17 19 20 21 22 23 24 28 29 31 35 37 38 40 41 43 51
    [20] 54 56 58 61 63 64 65 66 73 75 76 79 82 83 84 93 94 97 101
    [39] 103 105 106 108 113 115 117 118 119 123 124 128 131 132 133 134 135 137 138
    [58] 141 148 152 153 155 159 160 167 169 177 178 179 187 188 191 194 196 198
    
    $OOBdata[[3]]
     [1] 4 6 7 12 14 16 17 26 31 32 35 36 37 38 39 41 43 46 49
    [20] 53 54 55 58 59 60 62 64 69 72 79 86 87 88 92 97 98 103 104
    [39] 105 108 110 115 116 117 120 122 124 125 128 129 131 134 141 142 145 146 153
    [58] 155 156 158 160 161 164 178 179 180 182 184 186 188 194 197 198 199 200
    
    $OOBdata[[4]]
     [1] 4 8 9 12 13 18 23 26 27 29 30 31 35 40 45 47 48 50 52
    [20] 55 57 58 61 64 65 67 69 71 72 77 84 86 90 92 94 98 99 101
    [39] 102 103 105 109 114 115 123 125 126 127 129 130 134 139 142 145 146 148 149
    [58] 150 152 153 160 164 166 173 176 180 181 182 185 186 188 189 190 197
    
    $OOBdata[[5]]
     [1] 5 13 15 19 20 21 24 25 34 35 36 38 42 45 46 47 48 49 50
    [20] 51 52 55 59 61 64 66 67 69 71 75 77 84 85 90 94 96 101 103
    [39] 105 106 107 112 114 115 120 121 130 132 133 136 139 142 143 144 149 153 154
    [58] 156 157 160 161 165 167 172 179 184 185 186 189 193 199
    
    $OOBdata[[6]]
     [1] 2 10 11 13 18 21 22 25 32 33 35 37 44 47 51 58 59 61 62
    [20] 64 66 70 72 78 79 81 90 91 92 93 94 99 102 103 106 107 108 109
    [39] 110 113 115 116 119 121 122 124 126 127 128 129 131 134 137 141 142 144 147
    [58] 150 153 155 159 166 168 172 175 177 178 180 183 186 187 188 189 194
    
    $OOBdata[[7]]
     [1] 2 3 5 11 14 16 17 23 24 25 27 28 30 34 37 38 45 47 53
    [20] 54 62 67 73 78 79 80 82 84 86 88 90 93 97 99 104 111 115 119
    [39] 121 122 125 126 127 130 131 132 133 136 137 139 142 143 144 147 149 152 154
    [58] 155 162 163 167 186 190 192 195 198 199 200
    
    $OOBdata[[8]]
     [1] 1 5 6 7 9 11 13 14 16 18 19 22 32 34 38 41 42 43 44
    [20] 45 46 47 48 49 51 52 57 58 60 64 68 69 71 72 74 83 91 92
    [39] 96 98 99 102 106 107 114 116 120 123 129 133 139 148 154 160 162 165 172
    [58] 173 176 178 179 183 186 189 191 193 194 197
    
    $OOBdata[[9]]
     [1] 2 8 9 13 14 15 17 22 23 28 30 32 33 34 35 36 37 40 44
    [20] 46 47 48 50 55 58 60 66 68 72 73 74 76 78 81 83 84 86 87
    [39] 88 92 93 95 101 103 107 108 109 115 118 120 122 123 124 127 133 137 141
    [58] 143 144 146 148 149 151 155 162 163 170 176 181 185 186 189 195
    
    $OOBdata[[10]]
     [1] 4 5 12 13 15 17 20 23 25 27 30 31 32 40 41 42 43 45 46
    [20] 47 49 51 56 57 62 63 66 73 75 76 77 78 83 85 86 89 90 94
    [39] 95 99 101 103 106 110 114 119 121 124 132 136 137 139 144 146 147 148 150
    [58] 151 155 157 158 159 160 161 163 165 166 167 168 169 170 173 176 177 179 181
    [77] 182 183 190 191
    
    $OOBdata[[11]]
     [1] 1 3 4 6 9 12 13 15 24 25 27 28 29 30 33 35 36 38 40
    [20] 41 45 46 47 48 49 54 61 62 65 66 67 76 81 82 97 105 107 114
    [39] 116 119 122 126 128 129 134 138 139 140 142 147 148 151 152 153 155 163 164
    [58] 165 174 175 179 180 184 188 193 195 200
    
    $OOBdata[[12]]
     [1] 1 3 6 10 12 13 14 17 19 20 21 23 24 26 28 32 33 42 43
    [20] 45 47 50 54 56 59 60 62 63 64 65 67 68 70 71 84 89 91 92
    [39] 94 95 96 97 105 106 109 112 113 114 115 119 120 128 130 131 132 136 137
    [58] 139 146 152 157 158 159 163 166 167 168 170 178 179 185 186 194 200
    
    $OOBdata[[13]]
     [1] 1 2 3 5 6 7 11 13 16 18 20 21 25 26 28 32 37 38 41
    [20] 43 45 46 47 48 49 54 60 63 67 71 78 79 83 84 85 86 92 93
    [39] 100 102 106 108 109 111 117 123 124 125 130 132 133 134 138 139 144 150 155
    [58] 158 159 161 162 163 164 167 169 170 172 173 174 175 176 177 191 194 200
    
    $OOBdata[[14]]
     [1] 1 3 4 5 12 16 19 20 25 30 38 44 45 51 54 59 60 62 63
    [20] 64 66 68 70 72 73 74 76 82 85 88 89 91 93 94 95 103 107 108
    [39] 111 117 118 120 122 123 125 130 133 134 142 143 150 151 152 155 156 157 161
    [58] 162 164 165 166 167 171 172 175 180 187 188 191 193 196 199 200
    
    $OOBdata[[15]]
     [1] 2 4 7 11 12 13 17 19 20 31 32 35 36 37 38 40 43 51 52
    [20] 53 54 56 57 58 62 63 64 67 68 71 75 77 81 85 86 87 90 93
    [39] 95 101 103 111 113 114 121 125 126 130 131 133 136 141 145 146 147 148 149
    [58] 153 156 157 167 169 172 174 176 177 178 183 186 193 194 195 197 199 200
    
    $OOBdata[[16]]
     [1] 4 7 9 13 14 15 17 22 25 26 28 29 32 39 41 47 48 50 58
    [20] 60 61 63 64 67 69 75 77 79 80 82 85 88 96 100 101 104 110 111
    [39] 112 113 117 122 123 124 126 127 128 129 132 137 139 144 146 147 148 149 150
    [58] 154 155 157 159 160 163 165 166 167 168 169 172 178 179 184 185 191 194 198
    [77] 199
    
    $OOBdata[[17]]
     [1] 5 8 13 20 22 23 31 32 33 34 36 37 39 41 45 48 52 56 59
    [20] 62 70 74 78 83 85 86 88 90 91 96 100 101 102 103 106 108 110 111
    [39] 113 114 116 118 119 123 127 129 130 131 132 144 145 149 151 152 156 157 158
    [58] 161 162 170 171 176 188 189 193 196 198 199
    
    $OOBdata[[18]]
     [1] 2 3 5 7 10 11 13 17 18 23 30 31 32 36 38 40 44 46 47
    [20] 51 55 66 69 70 72 77 79 80 81 83 84 86 91 94 103 104 108 109
    [39] 111 114 115 119 121 124 126 130 131 137 138 142 144 147 148 149 151 156 157
    [58] 160 162 164 165 166 168 169 171 173 177 179 180 181 187 188 189 194 196 197
    
    $OOBdata[[19]]
     [1] 1 3 6 8 10 11 12 13 14 15 16 17 18 24 25 27 28 29 31
    [20] 32 36 38 40 51 53 56 57 58 60 61 62 64 65 71 72 73 74 77
    [39] 79 80 85 87 91 92 93 94 99 104 107 109 110 112 113 114 116 117 118
    [58] 119 121 123 126 127 130 132 142 143 149 150 151 154 156 157 159 164 167 169
    [77] 176 177 179 181 186 188 195 198 199 200
    
    $OOBdata[[20]]
     [1] 3 4 5 11 14 18 20 22 25 28 29 30 32 34 36 38 39 44 45
    [20] 53 56 62 64 65 68 74 76 82 86 91 92 102 103 104 105 107 108 111
    [39] 117 124 127 128 133 134 135 136 137 139 142 149 153 155 164 167 169 173 176
    [58] 178 183 184 189 191 192 193 196 197 199 200
    
    
    $norm
    [1] TRUE
    
    $numout
    [1] 5
    
    $predictors
    [1] 50
    
    $Xs
     X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19 X20 X21
    36 0 1 1 1 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0
    44 1 1 0 1 1 1 1 1 1 0 0 0 0 1 0 0 0 1 1 0 1
    114 0 1 1 0 0 1 1 1 1 0 0 0 0 0 1 0 1 0 0 1 0
    133 0 1 0 0 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 1
    132 1 1 0 0 0 1 1 1 0 1 0 0 1 1 1 0 1 1 1 0 1
    9 0 0 0 1 1 0 0 1 0 0 0 1 1 0 0 1 1 0 1 1 0
    151 0 0 0 0 0 0 1 1 0 1 1 0 0 1 1 1 1 1 0 1 1
    172 0 0 1 0 0 0 1 1 1 0 0 0 1 1 1 0 1 0 1 1 1
    190 1 0 0 0 0 0 0 1 0 1 1 1 0 0 0 0 0 0 1 1 1
    160 0 1 1 0 0 1 0 0 0 1 0 1 0 1 1 1 0 0 1 1 0
    187 1 1 0 0 0 1 1 0 0 1 1 0 1 0 1 1 1 1 1 1 0
    57 0 1 1 1 1 1 0 1 1 0 1 0 1 0 0 0 0 0 1 0 0
    55 0 1 1 1 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1
    147 1 1 0 0 0 1 1 1 0 1 1 1 0 1 0 1 0 0 1 1 1
    99 1 1 1 1 0 1 1 0 1 0 0 1 1 1 1 0 0 0 1 1 1
    43 0 1 1 1 1 0 1 1 1 0 1 0 1 0 0 0 1 0 1 1 0
    140 1 1 0 0 0 1 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0
    78 0 0 0 1 1 0 0 1 0 1 1 0 0 0 1 1 0 1 1 1 1
    183 1 0 0 0 0 0 1 1 0 1 1 0 0 0 0 0 1 0 1 1 1
    10 1 0 0 1 1 0 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0
    97 0 0 1 1 0 1 1 0 1 0 0 1 0 0 1 0 1 0 1 1 0
    200 0 1 1 0 0 1 1 0 0 1 0 1 0 1 0 0 0 0 1 0 0
    131 0 0 1 0 0 1 0 0 0 1 1 1 1 1 0 1 1 1 1 0 0
    178 1 0 0 0 0 1 1 0 1 0 1 0 0 0 1 1 0 1 1 1 0
    153 1 0 0 0 0 1 1 1 0 1 0 0 1 1 1 1 1 0 1 1 1
    80 1 1 0 1 1 1 0 0 0 1 1 1 0 0 0 1 1 1 1 1 0
    90 0 1 1 1 1 0 0 0 0 1 0 1 0 1 0 1 0 1 1 0 1
    41 0 0 1 1 1 1 1 0 1 0 0 0 0 1 0 1 0 1 1 1 1
    75 1 1 0 1 1 1 1 0 0 1 1 1 0 1 0 0 0 0 1 1 1
    138 1 1 0 0 0 1 0 1 0 1 0 1 1 0 0 0 0 1 0 0 1
    141 0 0 1 0 0 0 1 1 0 1 0 0 0 1 0 0 0 0 1 0 0
    158 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 1 0 0 0 1
    21 1 0 0 1 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 1 0
    143 1 1 1 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 1 0 1
    148 1 1 1 0 0 0 0 0 0 1 0 1 0 0 1 1 1 0 1 1 1
    68 0 1 1 1 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 1 0
    198 1 0 0 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 0 0 1
    176 0 0 1 0 0 1 0 0 1 0 1 1 1 0 0 0 0 0 1 1 0
    188 0 0 1 0 0 1 0 1 0 1 0 0 1 1 0 0 1 0 1 1 1
    165 1 0 0 0 0 1 0 0 1 0 1 0 1 0 1 0 0 1 0 1 1
    180 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 0 0 1 1 0
    128 1 0 1 0 0 0 0 1 1 1 1 0 0 0 1 0 0 1 1 1 1
    101 0 0 0 0 1 1 1 1 1 0 0 1 1 0 1 1 0 0 0 0 0
    76 1 1 1 1 1 1 0 1 0 1 1 1 0 1 1 1 0 0 1 0 0
    189 1 1 0 0 0 1 0 0 0 1 0 1 0 1 0 1 0 1 0 0 0
    150 1 0 0 0 0 1 1 1 0 1 1 1 1 1 1 0 0 0 1 0 0
    72 0 1 1 1 1 1 0 0 0 1 0 1 1 0 1 1 1 1 0 1 1
    156 1 0 1 0 0 1 0 1 0 1 0 1 1 1 1 1 1 1 0 0 1
    86 0 0 0 1 1 1 1 0 0 1 1 0 0 1 1 0 0 0 0 1 1
    74 1 1 0 1 1 1 0 0 0 1 1 1 0 0 0 0 0 1 1 0 1
    13 1 0 1 1 1 1 0 0 0 0 0 1 0 1 1 0 1 1 1 0 0
    48 1 0 0 1 1 0 1 0 1 0 1 0 1 1 0 0 1 0 0 0 0
    169 1 1 1 0 0 0 1 0 1 0 0 1 1 0 0 0 1 1 1 1 0
    7 0 0 0 1 1 0 1 0 0 0 1 1 0 1 0 0 1 0 1 0 0
    116 0 1 0 0 0 1 0 0 1 0 0 0 1 1 1 1 1 1 1 1 1
    30 1 0 0 1 1 0 0 0 0 0 1 1 1 0 1 0 1 0 1 0 0
    125 1 0 1 0 0 1 1 1 1 1 1 1 0 0 0 1 1 1 0 0 1
    45 1 0 0 1 1 1 1 0 1 0 1 1 0 1 0 1 1 1 1 0 1
    79 1 0 1 1 1 1 1 0 0 1 1 0 0 1 0 1 0 1 1 1 0
    113 0 0 0 0 0 0 1 1 1 0 1 0 1 1 1 1 0 1 0 1 0
    4 1 0 1 1 1 0 0 1 0 0 0 1 0 1 1 0 1 0 0 0 1
    103 0 0 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 1 1 0 1
    8 1 0 1 1 1 1 0 0 0 0 1 1 1 0 1 0 0 0 1 1 1
    154 1 0 1 0 0 0 0 1 0 1 0 1 1 1 0 0 1 1 1 0 0
    11 1 0 0 1 1 0 0 1 0 0 1 1 0 0 0 1 0 0 1 0 0
    96 1 1 1 1 0 0 1 1 1 0 0 1 1 1 0 0 0 1 0 0 0
    31 0 1 1 1 1 0 0 1 1 0 0 1 1 0 1 0 0 1 0 1 0
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     X22 X23 X24 X25 X26 X27 X28 X29 X30 X31 X32 X33 X34 X35 X36 X37 X38 X39 X40
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    67 1 1 1 0 0 1 0 1 1 1 0 1 1 0 1 1 1 0 1
    98 1 0 0 1 1 1 0 0 0 0 1 1 1 1 0 1 0 1 1
    197 0 0 1 0 0 0 1 1 1 1 1 1 0 0 1 1 1 0 1
    42 1 0 1 1 0 0 1 1 0 1 1 1 1 0 0 0 1 0 1
    59 0 0 1 1 0 1 0 0 1 1 1 1 0 1 0 0 0 1 1
    177 0 1 1 1 1 0 1 1 0 0 0 0 1 1 0 1 0 0 1
    129 1 0 1 0 1 1 1 0 1 0 0 0 0 0 0 0 1 0 1
     X41 X42 X43 X44 X45 X46 X47 X48 X49 X50
    36 0 0 0 0 1 1 1 0 1 1
    44 0 0 0 0 1 0 0 1 0 1
    114 0 1 1 1 1 1 0 1 0 1
    133 0 1 1 0 1 0 0 0 1 1
    132 0 0 1 0 0 1 1 1 1 0
    9 0 0 1 0 0 0 1 1 1 1
    151 1 1 0 1 0 1 0 1 0 0
    172 1 1 0 0 1 0 1 1 0 1
    190 0 1 0 0 1 0 1 0 1 1
    160 1 0 0 1 1 0 0 0 1 1
    187 0 1 1 0 1 0 0 1 1 0
    57 1 1 0 0 1 1 1 0 1 1
    55 1 1 1 1 0 0 0 1 1 1
    147 1 1 1 1 0 0 1 1 0 0
    99 0 1 0 0 0 1 0 0 0 0
    43 1 1 1 0 0 1 0 0 1 1
    140 0 1 0 1 0 1 0 0 1 1
    78 1 0 1 0 0 0 1 0 0 1
    183 1 1 0 1 1 0 1 0 0 0
    10 1 1 0 1 0 1 1 1 1 0
    97 1 0 0 0 0 0 1 1 0 0
    200 0 1 1 1 0 0 0 1 0 0
    131 1 1 1 0 0 1 1 0 1 0
    178 0 0 1 0 1 1 0 1 0 0
    153 0 0 1 0 1 1 1 0 1 0
    80 0 0 1 0 1 1 0 1 1 1
    90 0 1 1 0 0 1 0 1 0 1
    41 1 1 1 1 0 0 1 0 0 1
    75 1 1 0 0 0 0 1 1 0 1
    138 0 0 0 0 0 0 0 1 1 1
    141 1 0 1 1 1 0 1 1 1 0
    158 1 0 1 0 1 1 1 0 0 1
    21 1 0 0 1 0 1 1 1 1 1
    143 0 1 0 1 1 1 1 1 1 0
    148 0 0 0 1 0 0 1 0 0 1
    68 0 0 0 1 1 0 1 0 0 0
    198 1 0 1 1 0 1 0 0 0 0
    176 1 1 0 0 0 1 1 1 0 0
    188 1 0 1 0 1 0 1 1 1 0
    165 0 1 1 0 1 1 0 1 0 0
    180 1 0 1 0 1 0 0 1 1 0
    128 1 0 1 0 0 0 0 1 1 1
    101 1 0 0 0 1 0 1 0 0 0
    76 0 0 1 0 1 1 1 0 1 0
    189 0 1 1 0 1 0 1 0 1 0
    150 1 1 0 1 0 1 0 1 0 0
    72 1 1 0 1 0 1 0 1 1 1
    156 1 1 0 1 0 0 1 1 1 1
    86 1 0 1 0 0 0 1 1 0 1
    74 1 1 1 0 1 1 0 0 1 1
    13 1 0 1 1 1 0 1 0 1 1
    48 0 0 0 1 1 1 0 0 1 1
    169 1 1 0 0 1 1 1 0 0 0
    7 0 0 0 0 0 0 0 0 1 0
    116 1 0 0 0 0 0 0 1 0 0
    30 1 0 1 1 1 0 0 0 0 1
    125 1 1 1 1 1 0 0 0 0 1
    45 0 1 1 0 1 1 1 1 0 1
    79 0 0 1 1 0 0 1 1 0 0
    113 1 0 1 1 1 0 0 1 1 0
    4 0 0 1 0 0 1 0 0 1 1
    103 1 0 1 1 0 0 1 1 1 1
    8 1 1 0 0 1 1 0 0 1 1
    154 1 0 0 1 1 0 1 1 0 1
    11 0 0 0 1 1 0 0 1 1 1
    96 0 1 1 1 0 0 0 1 0 1
    31 0 1 0 0 0 0 0 1 0 1
    89 1 1 0 1 1 1 0 1 1 0
    64 0 0 0 1 0 0 0 1 0 1
    33 0 1 0 0 0 1 1 1 0 1
    65 0 1 0 0 1 0 1 0 0 1
    50 0 0 0 0 0 1 1 1 0 1
    37 1 0 1 1 0 1 0 0 1 1
    196 1 1 1 0 0 0 1 0 0 0
    38 0 1 1 1 0 1 0 0 1 1
    166 1 1 1 0 1 0 0 0 0 0
    135 0 1 0 1 0 1 0 1 0 0
    71 1 0 0 1 0 0 1 1 1 1
    119 0 0 1 0 1 0 0 1 0 1
    92 0 0 0 0 1 0 1 0 1 1
    63 1 1 1 1 0 0 0 1 0 1
    19 1 0 1 0 1 0 1 0 1 1
    123 0 1 1 1 0 1 0 0 1 1
    1 1 1 0 0 0 0 0 0 0 0
    47 0 0 1 0 0 1 1 0 0 1
    5 0 1 0 0 0 0 0 0 0 1
    70 1 0 0 0 1 1 0 0 1 1
    35 1 0 0 0 1 0 0 0 1 1
    17 0 0 1 1 1 1 0 1 0 1
    16 1 0 0 0 0 0 1 1 0 1
    62 0 0 0 0 0 0 1 0 1 1
    193 1 0 1 0 0 1 1 0 0 0
    24 1 0 1 1 1 1 0 1 0 0
    56 1 1 0 1 1 1 0 0 1 1
    28 1 0 0 0 0 1 1 0 0 1
    26 0 0 1 0 0 0 0 1 0 0
    115 0 0 1 0 0 1 0 1 0 1
    14 0 1 0 1 1 1 0 1 0 1
    102 1 1 1 1 0 0 0 0 0 0
    168 1 0 1 1 0 1 1 1 0 1
    124 1 0 1 1 1 0 1 0 1 1
    144 0 1 0 1 1 1 1 0 0 0
    167 0 0 1 0 1 0 1 0 0 0
    174 1 0 0 1 1 0 0 1 0 1
    81 0 1 1 0 1 1 0 0 0 1
    195 1 0 1 0 1 0 0 0 1 0
    25 0 0 0 1 0 1 1 0 1 1
    23 1 0 1 0 0 0 0 0 1 1
    112 0 1 1 0 1 1 0 0 1 0
    192 1 1 1 1 1 0 0 1 0 0
    142 0 0 1 0 1 1 0 1 1 1
    184 0 0 1 0 0 1 0 1 1 1
    137 1 0 1 0 1 1 0 1 0 1
    136 0 0 1 1 1 0 1 0 0 0
    171 1 0 0 1 1 0 1 0 0 0
    73 1 0 1 1 1 0 0 1 1 1
    185 0 0 0 1 1 1 1 1 0 1
    179 1 1 0 0 1 1 0 0 0 0
    149 1 1 1 0 0 1 1 1 0 1
    118 1 1 0 1 1 1 1 0 0 0
    106 1 0 1 0 1 1 0 0 0 1
    15 1 0 1 1 1 1 1 0 0 1
    122 1 0 0 0 1 1 1 0 0 1
    18 0 0 0 1 1 1 1 0 0 1
    161 1 0 0 1 1 1 0 0 1 1
    88 1 0 0 0 0 1 1 0 1 0
    49 0 0 0 1 0 1 0 0 0 1
    34 0 1 1 1 1 1 0 0 0 1
    164 1 1 0 0 1 0 0 1 1 1
    155 1 0 0 1 0 1 1 0 1 0
    134 0 1 1 0 0 0 0 0 1 0
    181 1 0 0 1 0 0 1 0 0 0
    95 1 0 1 0 1 0 0 0 1 0
    51 1 0 0 1 0 1 0 0 0 1
    69 0 0 1 1 0 0 1 0 1 1
    82 1 0 1 0 1 1 0 0 0 1
    139 0 1 0 0 1 1 1 0 1 1
    27 1 1 1 0 1 0 0 0 1 1
    87 0 0 1 1 1 1 0 1 0 1
    66 0 0 0 1 1 1 0 0 0 0
    146 0 1 0 0 0 0 1 1 1 1
    110 1 1 1 0 0 1 0 0 0 1
    3 0 1 0 1 1 0 0 0 1 1
    61 0 1 0 1 1 0 0 0 1 1
    85 1 0 0 0 0 0 0 1 0 1
    53 0 0 0 1 0 1 1 0 1 1
    173 1 1 0 1 0 1 1 0 0 0
    127 0 1 1 1 1 0 1 0 0 1
    52 1 0 1 1 0 1 1 0 0 0
    100 1 1 1 1 0 1 1 0 1 0
    40 0 0 0 0 1 0 1 0 1 1
    126 0 0 1 1 0 1 0 0 0 1
    54 1 0 0 1 1 0 1 0 0 1
    32 1 1 0 1 0 1 0 0 0 1
    22 1 1 0 1 0 0 1 0 0 1
    104 0 1 0 1 0 0 0 0 1 1
    107 1 1 0 0 0 1 1 0 0 0
    170 1 1 1 0 0 1 1 1 0 1
    46 0 1 1 0 1 1 0 0 0 1
    157 0 1 0 1 1 1 1 0 1 1
    58 1 0 0 1 1 0 0 1 1 1
    120 1 1 0 1 0 0 1 1 0 0
    145 1 0 1 1 1 0 1 1 0 0
    108 1 0 0 0 0 1 1 0 1 0
    91 0 1 0 1 1 1 0 0 0 1
    159 0 1 1 1 0 1 0 1 0 1
    93 0 0 1 0 1 1 1 1 1 1
    77 1 1 1 1 0 0 0 1 1 1
    2 1 1 1 1 1 0 0 1 1 1
    83 0 1 0 0 1 1 0 1 0 1
    111 1 0 1 1 0 0 1 0 1 0
    182 0 1 1 0 0 0 0 0 1 0
    130 1 0 0 0 1 1 1 1 1 1
    191 1 1 1 0 1 0 1 0 0 0
    105 1 0 0 0 0 0 1 0 0 0
    94 0 1 0 0 1 1 1 1 0 1
    20 0 0 1 1 1 1 0 1 0 1
    121 0 1 1 1 0 1 0 0 1 1
    186 0 1 0 1 0 1 1 1 0 0
    109 0 1 1 1 0 1 1 1 1 1
    162 1 1 0 1 1 1 1 0 1 0
    6 0 1 0 1 1 0 1 1 1 1
    117 0 0 0 0 1 0 0 0 0 0
    84 1 0 0 1 1 0 1 0 1 1
    152 0 0 1 0 1 0 1 1 1 0
    163 1 0 1 0 1 0 1 1 1 0
    194 0 0 1 0 0 0 1 0 1 0
    175 0 0 0 0 1 0 1 0 1 0
    60 1 0 0 0 1 1 0 0 1 1
    29 0 0 1 1 1 1 0 1 0 1
    39 0 0 0 0 0 0 0 0 0 1
    199 1 0 0 0 1 0 0 1 0 0
    12 0 0 1 0 0 1 0 0 0 1
    67 0 1 0 0 0 1 0 0 0 1
    98 1 0 0 1 1 0 1 1 1 0
    197 1 1 1 0 0 0 1 1 1 0
    42 0 0 0 0 0 1 1 0 1 1
    59 1 0 1 1 0 0 1 1 1 1
    177 0 1 0 1 1 0 1 0 1 1
    129 0 1 0 0 1 1 1 1 1 1
    
    attr(,"class")
    [1] "logforest"
    > predict(LF.fit1)
    Error in UseMethod("predict") :
     no applicable method for 'predict' applied to an object of class "logforest"
    Calls: predict
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64