Classical Factor Analysis
FaClassic.RdPerforms a classical factor analysis and returns the results as an object of class "FaClassic" (a.k.a. constructor).
Usage
FaClassic(x, ...)
# S3 method for class 'formula'
FaClassic(formula, data = NULL, factors = 2, cor = FALSE, method = "mle",
scoresMethod = "none", ...)
# Default S3 method
FaClassic(x, factors = 2, cor = FALSE, method = c("mle", "pca", "pfa"),
scoresMethod = c("none", "regression", "Bartlett"), ...)Arguments
- x
A formula or a numeric matrix or an object that can be coerced to a numeric matrix.
- ...
Arguments passed to or from other methods.
- formula
A formula with no response variable, referring only to numeric variables.
- data
An optional data frame (or similar: see
model.frame) containing the variables in theformula.- factors
The number of factors to be fitted.
- cor
A logical value indicating whether the calculation should use the covariance matrix (
cor = FALSE) or the correlation matrix (cor = TRUE).- method
The method of factor analysis, one of "mle" (the default), "pca", and "pfa".
- scoresMethod
Type of scores to produce, if any. The default is
"none","regression"gives Thompson's scores,"Bartlett"gives Bartlett's weighted least-squares scores.
Value
An S4 object of class FaClassic-class which is a subclass of the virtual class Fa-class.
Author
Ying-Ying Zhang (Robert) robertzhangyying@qq.com
Examples
data("hbk")
hbk.x = hbk[,1:3]
## faClassicPcaReg uses the default method
faClassicPcaReg = FaClassic(x = hbk.x, factors = 2, method = "pca",
scoresMethod = "regression"); faClassicPcaReg
#> An object of class "FaClassic"
#> Slot "call":
#> FaClassic(x = hbk.x, factors = 2, method = "pca", scoresMethod = "regression")
#>
#> Slot "converged":
#> NULL
#>
#> Slot "loadings":
#> Factor1 Factor2
#> X1 3.411036 0.936662
#> X2 7.278529 3.860723
#> X3 11.270812 3.273734
#>
#> Slot "communality":
#> X1 X2 X3
#> 12.51250 67.88217 137.74853
#>
#> Slot "uniquenesses":
#> X1 X2 X3
#> 0.8292095832 0.0007959085 0.0863235416
#>
#> Slot "cor":
#> [1] FALSE
#>
#> Slot "covariance":
#> X1 X2 X3
#> X1 13.34171 28.46921 41.24398
#> X2 28.46921 67.88297 94.66562
#> X3 41.24398 94.66562 137.83486
#>
#> Slot "correlation":
#> X1 X2 X3
#> X1 1.0000000 0.9459958 0.9617790
#> X2 0.9459958 1.0000000 0.9786612
#> X3 0.9617790 0.9786612 1.0000000
#>
#> Slot "usedMatrix":
#> X1 X2 X3
#> X1 13.34171 28.46921 41.24398
#> X2 28.46921 67.88297 94.66562
#> X3 41.24398 94.66562 137.83486
#>
#> Slot "reducedCorrelation":
#> NULL
#>
#> Slot "criteria":
#> NULL
#>
#> Slot "factors":
#> [1] 2
#>
#> Slot "dof":
#> NULL
#>
#> Slot "method":
#> [1] "pca"
#>
#> Slot "scores":
#> Factor1 Factor2
#> [1,] 1.836216178 0.161337548
#> [2,] 1.756800683 0.549735006
#> [3,] 2.250318962 -0.462115084
#> [4,] 2.110379324 0.145591275
#> [5,] 2.095218367 0.066345803
#> [6,] 1.906582805 0.232737572
#> [7,] 1.788199906 0.587263155
#> [8,] 1.911901278 0.021274118
#> [9,] 2.106202931 -0.053757894
#> [10,] 2.122518267 -0.342046036
#> [11,] 2.348800415 0.342830312
#> [12,] 2.927387983 -1.009336488
#> [13,] 1.905818664 1.685956006
#> [14,] 0.528829255 6.359573459
#> [15,] -0.448347445 0.133780216
#> [16,] -0.668908585 0.366404244
#> [17,] -0.779858578 0.442576537
#> [18,] -0.320380311 -0.436151460
#> [19,] -0.697421067 0.621061863
#> [20,] -0.531502346 0.422359906
#> [21,] -0.418046839 -0.099159644
#> [22,] -0.718663795 0.742356037
#> [23,] -0.665393822 0.394816805
#> [24,] -0.761582949 0.580540198
#> [25,] -0.419693120 -0.657298051
#> [26,] -0.598455877 0.539385243
#> [27,] -0.247874654 -0.345083251
#> [28,] -0.219836054 -0.829109302
#> [29,] -0.484797036 -0.302159906
#> [30,] 0.006043560 -1.273196784
#> [31,] -0.414104099 -0.319367475
#> [32,] -0.862788836 0.802561432
#> [33,] -0.704564559 0.680970529
#> [34,] -0.404005807 -0.681812987
#> [35,] -0.226207238 -0.410125033
#> [36,] -0.370021556 -0.176933456
#> [37,] -0.581066520 0.435007090
#> [38,] -0.621218623 0.029086231
#> [39,] -0.210664210 -1.057488778
#> [40,] -0.638509599 0.278324368
#> [41,] -0.093737402 -0.869315133
#> [42,] -0.222301393 -0.760169894
#> [43,] -0.929819437 1.166157588
#> [44,] 0.040846868 -1.395395068
#> [45,] -0.345171409 -0.777979662
#> [46,] 0.005618871 -1.329449176
#> [47,] -0.241826492 -0.980332711
#> [48,] -0.094700744 -0.865086128
#> [49,] -0.436399538 0.009447513
#> [50,] -0.371498956 -0.025665034
#> [51,] -0.585765982 0.034545544
#> [52,] -0.234984713 -0.865075764
#> [53,] -0.017987529 -1.299228393
#> [54,] -0.924264023 1.069378350
#> [55,] -0.757104843 0.604723754
#> [56,] -0.808109523 0.898476392
#> [57,] -0.432379728 -0.457331137
#> [58,] -0.698147469 0.739975084
#> [59,] -0.269779011 -0.394725685
#> [60,] -0.198808958 -0.673656887
#> [61,] -0.557786430 0.493393901
#> [62,] -0.459937878 -0.555054318
#> [63,] -0.892563087 0.931740886
#> [64,] -0.361028449 0.001270686
#> [65,] -0.067714855 -1.141591364
#> [66,] -0.694666313 0.333677831
#> [67,] -0.570392680 0.141917212
#> [68,] -0.352127153 -0.776502820
#> [69,] -0.474012517 -0.407110790
#> [70,] -0.340986005 -0.230478698
#> [71,] -0.421675567 -0.010838417
#> [72,] -0.579475155 0.167004879
#> [73,] -0.425439569 -0.197214204
#> [74,] -0.631892463 0.322176109
#> [75,] -0.141285522 -1.068417769
#>
#> Slot "scoresMethod":
#> [1] "regression"
#>
#> Slot "scoringCoef":
#> X1 X2 X3
#> Factor1 0.06192447 -0.1643831 0.1761400
#> Factor2 -0.12400651 0.5687014 -0.3297295
#>
#> Slot "meanF":
#> Factor1 Factor2
#> 1.473636e-15 -2.560914e-15
#>
#> Slot "corF":
#> Factor1 Factor2
#> Factor1 1.000000e+00 5.144533e-15
#> Factor2 5.144533e-15 1.000000e+00
#>
#> Slot "STATISTIC":
#> NULL
#>
#> Slot "PVAL":
#> NULL
#>
#> Slot "n.obs":
#> [1] 75
#>
#> Slot "center":
#> X1 X2 X3
#> 3.206667 5.597333 7.230667
#>
#> Slot "eigenvalues":
#> [1] 216.162129 1.981077 0.916329
#>
#> Slot "cov.control":
#> NULL
#>
summary(faClassicPcaReg)
#> An object of class "SummaryFa"
#> Slot "faobj":
#> An object of class "FaClassic"
#> Slot "call":
#> FaClassic(x = hbk.x, factors = 2, method = "pca", scoresMethod = "regression")
#>
#> Slot "converged":
#> NULL
#>
#> Slot "loadings":
#> Factor1 Factor2
#> X1 3.411036 0.936662
#> X2 7.278529 3.860723
#> X3 11.270812 3.273734
#>
#> Slot "communality":
#> X1 X2 X3
#> 12.51250 67.88217 137.74853
#>
#> Slot "uniquenesses":
#> X1 X2 X3
#> 0.8292095832 0.0007959085 0.0863235416
#>
#> Slot "cor":
#> [1] FALSE
#>
#> Slot "covariance":
#> X1 X2 X3
#> X1 13.34171 28.46921 41.24398
#> X2 28.46921 67.88297 94.66562
#> X3 41.24398 94.66562 137.83486
#>
#> Slot "correlation":
#> X1 X2 X3
#> X1 1.0000000 0.9459958 0.9617790
#> X2 0.9459958 1.0000000 0.9786612
#> X3 0.9617790 0.9786612 1.0000000
#>
#> Slot "usedMatrix":
#> X1 X2 X3
#> X1 13.34171 28.46921 41.24398
#> X2 28.46921 67.88297 94.66562
#> X3 41.24398 94.66562 137.83486
#>
#> Slot "reducedCorrelation":
#> NULL
#>
#> Slot "criteria":
#> NULL
#>
#> Slot "factors":
#> [1] 2
#>
#> Slot "dof":
#> NULL
#>
#> Slot "method":
#> [1] "pca"
#>
#> Slot "scores":
#> Factor1 Factor2
#> [1,] 1.836216178 0.161337548
#> [2,] 1.756800683 0.549735006
#> [3,] 2.250318962 -0.462115084
#> [4,] 2.110379324 0.145591275
#> [5,] 2.095218367 0.066345803
#> [6,] 1.906582805 0.232737572
#> [7,] 1.788199906 0.587263155
#> [8,] 1.911901278 0.021274118
#> [9,] 2.106202931 -0.053757894
#> [10,] 2.122518267 -0.342046036
#> [11,] 2.348800415 0.342830312
#> [12,] 2.927387983 -1.009336488
#> [13,] 1.905818664 1.685956006
#> [14,] 0.528829255 6.359573459
#> [15,] -0.448347445 0.133780216
#> [16,] -0.668908585 0.366404244
#> [17,] -0.779858578 0.442576537
#> [18,] -0.320380311 -0.436151460
#> [19,] -0.697421067 0.621061863
#> [20,] -0.531502346 0.422359906
#> [21,] -0.418046839 -0.099159644
#> [22,] -0.718663795 0.742356037
#> [23,] -0.665393822 0.394816805
#> [24,] -0.761582949 0.580540198
#> [25,] -0.419693120 -0.657298051
#> [26,] -0.598455877 0.539385243
#> [27,] -0.247874654 -0.345083251
#> [28,] -0.219836054 -0.829109302
#> [29,] -0.484797036 -0.302159906
#> [30,] 0.006043560 -1.273196784
#> [31,] -0.414104099 -0.319367475
#> [32,] -0.862788836 0.802561432
#> [33,] -0.704564559 0.680970529
#> [34,] -0.404005807 -0.681812987
#> [35,] -0.226207238 -0.410125033
#> [36,] -0.370021556 -0.176933456
#> [37,] -0.581066520 0.435007090
#> [38,] -0.621218623 0.029086231
#> [39,] -0.210664210 -1.057488778
#> [40,] -0.638509599 0.278324368
#> [41,] -0.093737402 -0.869315133
#> [42,] -0.222301393 -0.760169894
#> [43,] -0.929819437 1.166157588
#> [44,] 0.040846868 -1.395395068
#> [45,] -0.345171409 -0.777979662
#> [46,] 0.005618871 -1.329449176
#> [47,] -0.241826492 -0.980332711
#> [48,] -0.094700744 -0.865086128
#> [49,] -0.436399538 0.009447513
#> [50,] -0.371498956 -0.025665034
#> [51,] -0.585765982 0.034545544
#> [52,] -0.234984713 -0.865075764
#> [53,] -0.017987529 -1.299228393
#> [54,] -0.924264023 1.069378350
#> [55,] -0.757104843 0.604723754
#> [56,] -0.808109523 0.898476392
#> [57,] -0.432379728 -0.457331137
#> [58,] -0.698147469 0.739975084
#> [59,] -0.269779011 -0.394725685
#> [60,] -0.198808958 -0.673656887
#> [61,] -0.557786430 0.493393901
#> [62,] -0.459937878 -0.555054318
#> [63,] -0.892563087 0.931740886
#> [64,] -0.361028449 0.001270686
#> [65,] -0.067714855 -1.141591364
#> [66,] -0.694666313 0.333677831
#> [67,] -0.570392680 0.141917212
#> [68,] -0.352127153 -0.776502820
#> [69,] -0.474012517 -0.407110790
#> [70,] -0.340986005 -0.230478698
#> [71,] -0.421675567 -0.010838417
#> [72,] -0.579475155 0.167004879
#> [73,] -0.425439569 -0.197214204
#> [74,] -0.631892463 0.322176109
#> [75,] -0.141285522 -1.068417769
#>
#> Slot "scoresMethod":
#> [1] "regression"
#>
#> Slot "scoringCoef":
#> X1 X2 X3
#> Factor1 0.06192447 -0.1643831 0.1761400
#> Factor2 -0.12400651 0.5687014 -0.3297295
#>
#> Slot "meanF":
#> Factor1 Factor2
#> 1.473636e-15 -2.560914e-15
#>
#> Slot "corF":
#> Factor1 Factor2
#> Factor1 1.000000e+00 5.144533e-15
#> Factor2 5.144533e-15 1.000000e+00
#>
#> Slot "STATISTIC":
#> NULL
#>
#> Slot "PVAL":
#> NULL
#>
#> Slot "n.obs":
#> [1] 75
#>
#> Slot "center":
#> X1 X2 X3
#> 3.206667 5.597333 7.230667
#>
#> Slot "eigenvalues":
#> [1] 216.162129 1.981077 0.916329
#>
#> Slot "cov.control":
#> NULL
#>
#>
#> Slot "importance":
#> Factor1 Factor2
#> SS loadings 191.643 26.500
#> Proportion Var 0.875 0.121
#> Cumulative Var 0.875 0.996
#>
## faClassicForPcaReg uses the formula interface
## faClassicForPcaReg = faClassicPcaReg
faClassicForPcaReg = FaClassic(~., data=as.data.frame(hbk.x), factors = 2,
method = "pca", scoresMethod = "regression"); faClassicForPcaReg
#> An object of class "FaClassic"
#> Slot "call":
#> FaClassic(formula = ~., data = as.data.frame(hbk.x), factors = 2,
#> method = "pca", scoresMethod = "regression")
#>
#> Slot "converged":
#> NULL
#>
#> Slot "loadings":
#> Factor1 Factor2
#> X1 3.411036 0.936662
#> X2 7.278529 3.860723
#> X3 11.270812 3.273734
#>
#> Slot "communality":
#> X1 X2 X3
#> 12.51250 67.88217 137.74853
#>
#> Slot "uniquenesses":
#> X1 X2 X3
#> 0.8292095832 0.0007959085 0.0863235416
#>
#> Slot "cor":
#> [1] FALSE
#>
#> Slot "covariance":
#> X1 X2 X3
#> X1 13.34171 28.46921 41.24398
#> X2 28.46921 67.88297 94.66562
#> X3 41.24398 94.66562 137.83486
#>
#> Slot "correlation":
#> X1 X2 X3
#> X1 1.0000000 0.9459958 0.9617790
#> X2 0.9459958 1.0000000 0.9786612
#> X3 0.9617790 0.9786612 1.0000000
#>
#> Slot "usedMatrix":
#> X1 X2 X3
#> X1 13.34171 28.46921 41.24398
#> X2 28.46921 67.88297 94.66562
#> X3 41.24398 94.66562 137.83486
#>
#> Slot "reducedCorrelation":
#> NULL
#>
#> Slot "criteria":
#> NULL
#>
#> Slot "factors":
#> [1] 2
#>
#> Slot "dof":
#> NULL
#>
#> Slot "method":
#> [1] "pca"
#>
#> Slot "scores":
#> Factor1 Factor2
#> 1 1.836216178 0.161337548
#> 2 1.756800683 0.549735006
#> 3 2.250318962 -0.462115084
#> 4 2.110379324 0.145591275
#> 5 2.095218367 0.066345803
#> 6 1.906582805 0.232737572
#> 7 1.788199906 0.587263155
#> 8 1.911901278 0.021274118
#> 9 2.106202931 -0.053757894
#> 10 2.122518267 -0.342046036
#> 11 2.348800415 0.342830312
#> 12 2.927387983 -1.009336488
#> 13 1.905818664 1.685956006
#> 14 0.528829255 6.359573459
#> 15 -0.448347445 0.133780216
#> 16 -0.668908585 0.366404244
#> 17 -0.779858578 0.442576537
#> 18 -0.320380311 -0.436151460
#> 19 -0.697421067 0.621061863
#> 20 -0.531502346 0.422359906
#> 21 -0.418046839 -0.099159644
#> 22 -0.718663795 0.742356037
#> 23 -0.665393822 0.394816805
#> 24 -0.761582949 0.580540198
#> 25 -0.419693120 -0.657298051
#> 26 -0.598455877 0.539385243
#> 27 -0.247874654 -0.345083251
#> 28 -0.219836054 -0.829109302
#> 29 -0.484797036 -0.302159906
#> 30 0.006043560 -1.273196784
#> 31 -0.414104099 -0.319367475
#> 32 -0.862788836 0.802561432
#> 33 -0.704564559 0.680970529
#> 34 -0.404005807 -0.681812987
#> 35 -0.226207238 -0.410125033
#> 36 -0.370021556 -0.176933456
#> 37 -0.581066520 0.435007090
#> 38 -0.621218623 0.029086231
#> 39 -0.210664210 -1.057488778
#> 40 -0.638509599 0.278324368
#> 41 -0.093737402 -0.869315133
#> 42 -0.222301393 -0.760169894
#> 43 -0.929819437 1.166157588
#> 44 0.040846868 -1.395395068
#> 45 -0.345171409 -0.777979662
#> 46 0.005618871 -1.329449176
#> 47 -0.241826492 -0.980332711
#> 48 -0.094700744 -0.865086128
#> 49 -0.436399538 0.009447513
#> 50 -0.371498956 -0.025665034
#> 51 -0.585765982 0.034545544
#> 52 -0.234984713 -0.865075764
#> 53 -0.017987529 -1.299228393
#> 54 -0.924264023 1.069378350
#> 55 -0.757104843 0.604723754
#> 56 -0.808109523 0.898476392
#> 57 -0.432379728 -0.457331137
#> 58 -0.698147469 0.739975084
#> 59 -0.269779011 -0.394725685
#> 60 -0.198808958 -0.673656887
#> 61 -0.557786430 0.493393901
#> 62 -0.459937878 -0.555054318
#> 63 -0.892563087 0.931740886
#> 64 -0.361028449 0.001270686
#> 65 -0.067714855 -1.141591364
#> 66 -0.694666313 0.333677831
#> 67 -0.570392680 0.141917212
#> 68 -0.352127153 -0.776502820
#> 69 -0.474012517 -0.407110790
#> 70 -0.340986005 -0.230478698
#> 71 -0.421675567 -0.010838417
#> 72 -0.579475155 0.167004879
#> 73 -0.425439569 -0.197214204
#> 74 -0.631892463 0.322176109
#> 75 -0.141285522 -1.068417769
#>
#> Slot "scoresMethod":
#> [1] "regression"
#>
#> Slot "scoringCoef":
#> X1 X2 X3
#> Factor1 0.06192447 -0.1643831 0.1761400
#> Factor2 -0.12400651 0.5687014 -0.3297295
#>
#> Slot "meanF":
#> Factor1 Factor2
#> 1.473636e-15 -2.560914e-15
#>
#> Slot "corF":
#> Factor1 Factor2
#> Factor1 1.000000e+00 5.144533e-15
#> Factor2 5.144533e-15 1.000000e+00
#>
#> Slot "STATISTIC":
#> NULL
#>
#> Slot "PVAL":
#> NULL
#>
#> Slot "n.obs":
#> [1] 75
#>
#> Slot "center":
#> X1 X2 X3
#> 3.206667 5.597333 7.230667
#>
#> Slot "eigenvalues":
#> [1] 216.162129 1.981077 0.916329
#>
#> Slot "cov.control":
#> NULL
#>
summary(faClassicForPcaReg)
#> An object of class "SummaryFa"
#> Slot "faobj":
#> An object of class "FaClassic"
#> Slot "call":
#> FaClassic(formula = ~., data = as.data.frame(hbk.x), factors = 2,
#> method = "pca", scoresMethod = "regression")
#>
#> Slot "converged":
#> NULL
#>
#> Slot "loadings":
#> Factor1 Factor2
#> X1 3.411036 0.936662
#> X2 7.278529 3.860723
#> X3 11.270812 3.273734
#>
#> Slot "communality":
#> X1 X2 X3
#> 12.51250 67.88217 137.74853
#>
#> Slot "uniquenesses":
#> X1 X2 X3
#> 0.8292095832 0.0007959085 0.0863235416
#>
#> Slot "cor":
#> [1] FALSE
#>
#> Slot "covariance":
#> X1 X2 X3
#> X1 13.34171 28.46921 41.24398
#> X2 28.46921 67.88297 94.66562
#> X3 41.24398 94.66562 137.83486
#>
#> Slot "correlation":
#> X1 X2 X3
#> X1 1.0000000 0.9459958 0.9617790
#> X2 0.9459958 1.0000000 0.9786612
#> X3 0.9617790 0.9786612 1.0000000
#>
#> Slot "usedMatrix":
#> X1 X2 X3
#> X1 13.34171 28.46921 41.24398
#> X2 28.46921 67.88297 94.66562
#> X3 41.24398 94.66562 137.83486
#>
#> Slot "reducedCorrelation":
#> NULL
#>
#> Slot "criteria":
#> NULL
#>
#> Slot "factors":
#> [1] 2
#>
#> Slot "dof":
#> NULL
#>
#> Slot "method":
#> [1] "pca"
#>
#> Slot "scores":
#> Factor1 Factor2
#> 1 1.836216178 0.161337548
#> 2 1.756800683 0.549735006
#> 3 2.250318962 -0.462115084
#> 4 2.110379324 0.145591275
#> 5 2.095218367 0.066345803
#> 6 1.906582805 0.232737572
#> 7 1.788199906 0.587263155
#> 8 1.911901278 0.021274118
#> 9 2.106202931 -0.053757894
#> 10 2.122518267 -0.342046036
#> 11 2.348800415 0.342830312
#> 12 2.927387983 -1.009336488
#> 13 1.905818664 1.685956006
#> 14 0.528829255 6.359573459
#> 15 -0.448347445 0.133780216
#> 16 -0.668908585 0.366404244
#> 17 -0.779858578 0.442576537
#> 18 -0.320380311 -0.436151460
#> 19 -0.697421067 0.621061863
#> 20 -0.531502346 0.422359906
#> 21 -0.418046839 -0.099159644
#> 22 -0.718663795 0.742356037
#> 23 -0.665393822 0.394816805
#> 24 -0.761582949 0.580540198
#> 25 -0.419693120 -0.657298051
#> 26 -0.598455877 0.539385243
#> 27 -0.247874654 -0.345083251
#> 28 -0.219836054 -0.829109302
#> 29 -0.484797036 -0.302159906
#> 30 0.006043560 -1.273196784
#> 31 -0.414104099 -0.319367475
#> 32 -0.862788836 0.802561432
#> 33 -0.704564559 0.680970529
#> 34 -0.404005807 -0.681812987
#> 35 -0.226207238 -0.410125033
#> 36 -0.370021556 -0.176933456
#> 37 -0.581066520 0.435007090
#> 38 -0.621218623 0.029086231
#> 39 -0.210664210 -1.057488778
#> 40 -0.638509599 0.278324368
#> 41 -0.093737402 -0.869315133
#> 42 -0.222301393 -0.760169894
#> 43 -0.929819437 1.166157588
#> 44 0.040846868 -1.395395068
#> 45 -0.345171409 -0.777979662
#> 46 0.005618871 -1.329449176
#> 47 -0.241826492 -0.980332711
#> 48 -0.094700744 -0.865086128
#> 49 -0.436399538 0.009447513
#> 50 -0.371498956 -0.025665034
#> 51 -0.585765982 0.034545544
#> 52 -0.234984713 -0.865075764
#> 53 -0.017987529 -1.299228393
#> 54 -0.924264023 1.069378350
#> 55 -0.757104843 0.604723754
#> 56 -0.808109523 0.898476392
#> 57 -0.432379728 -0.457331137
#> 58 -0.698147469 0.739975084
#> 59 -0.269779011 -0.394725685
#> 60 -0.198808958 -0.673656887
#> 61 -0.557786430 0.493393901
#> 62 -0.459937878 -0.555054318
#> 63 -0.892563087 0.931740886
#> 64 -0.361028449 0.001270686
#> 65 -0.067714855 -1.141591364
#> 66 -0.694666313 0.333677831
#> 67 -0.570392680 0.141917212
#> 68 -0.352127153 -0.776502820
#> 69 -0.474012517 -0.407110790
#> 70 -0.340986005 -0.230478698
#> 71 -0.421675567 -0.010838417
#> 72 -0.579475155 0.167004879
#> 73 -0.425439569 -0.197214204
#> 74 -0.631892463 0.322176109
#> 75 -0.141285522 -1.068417769
#>
#> Slot "scoresMethod":
#> [1] "regression"
#>
#> Slot "scoringCoef":
#> X1 X2 X3
#> Factor1 0.06192447 -0.1643831 0.1761400
#> Factor2 -0.12400651 0.5687014 -0.3297295
#>
#> Slot "meanF":
#> Factor1 Factor2
#> 1.473636e-15 -2.560914e-15
#>
#> Slot "corF":
#> Factor1 Factor2
#> Factor1 1.000000e+00 5.144533e-15
#> Factor2 5.144533e-15 1.000000e+00
#>
#> Slot "STATISTIC":
#> NULL
#>
#> Slot "PVAL":
#> NULL
#>
#> Slot "n.obs":
#> [1] 75
#>
#> Slot "center":
#> X1 X2 X3
#> 3.206667 5.597333 7.230667
#>
#> Slot "eigenvalues":
#> [1] 216.162129 1.981077 0.916329
#>
#> Slot "cov.control":
#> NULL
#>
#>
#> Slot "importance":
#> Factor1 Factor2
#> SS loadings 191.643 26.500
#> Proportion Var 0.875 0.121
#> Cumulative Var 0.875 0.996
#>