Finding outliers of a sigle variable (y) by a regression model using a single explanatory variable (x).
OutlierRegression.Rdoutliers are found by using a limit for studentized residuals.
Usage
OutlierRegression(
data,
idName = names(data)[1],
strataName = NULL,
xName = names(data)[3],
yName = names(data)[4],
method = "ordinary",
limitModel = 2.5,
limitIterate = 4.5
)
OutlierRegressionMicro(...)
OutlierRegressionTall(..., iD = TalliD())
OutlierRegressionWide(
...,
addName = WideAddName(),
sep = WideSep(),
idNames = c("", "strata", ""),
addLast = FALSE
)Arguments
- data
Input data set of class data.frame
- idName
Name of id-variable(s)
- strataName
Name of starta-variable. Single strata when NULL (default)
- xName
Name of x-variable
- yName
Name of y-variable
- method
The method (model and weight) coded as a string: "ordinary" (default), "ratio", "noconstant", "mean" or "ratioconstant".
- limitModel
Studentized residuals limit. Above limit -> outlier.
- limitIterate
Studentized residuals limit for iterative calculation of studentized residuals.
Value
Output of OutlierRegression is a list of two data frames. The micro data frame has as many rows as input and aggregates data frame has one row for each strata. The individual variables are:
micro consists of the following elements:
- id
id from input
- x
The input x variable
- y
The input y variable
- strata
The input strata variable (can be NULL)
- outlier
Dummy variable: outlier (1) or not (0).
- category123
The three imputation groups: representative (1), correct but not representative (2), wrong (3).
- yHat
Fitted values
- rStud
The studentized residuals from last iteration
- dffits
The DFFITS statistic from last iteration
- hii
The leverages (diagonal elements of hat matrix) from last iteration
- leaveOutResid
The outside-model residual from last iteration
- limLo
-limitModel
- limUp
limitModel
aggregates consists of the following elements:
- N
Number of observations in each strata
- coef
The final first model coefficient
- coefB
The final second model coefficient or zeros when only one coefficient in model.
- nModel
The final number of observations in model.
- sigmaHat
The final square root of the estimated variance parameter
Output of OutlierRegressionMicro is the single data frame micro above.
Output of OutlierRegressionTall and OutlierRegressionWide are similiar to the
functions in ImputeRegression.
Details
This function is related to ImputeRegression
and the structure and the names of output are very similar.
Note that missing values of x are allowed here.
Examples
z = cbind(id=1:34,KostraData("ratioTest")[,c(3,1,2)])
OutlierRegression(z,strataName="k")
#> $micro
#> id x y strata yHat outlier rStud dffits
#> 1 1 1.1 2.300000e+00 1 2.360000 0 -3.825460e-01 -0.46852129
#> 2 2 2.2 3.100000e+00 1 2.860000 0 1.819435e+00 1.19110000
#> 3 3 3.3 3.200000e+00 1 3.360000 0 -8.000000e-01 -0.40000000
#> 4 4 4.4 3.700000e+00 1 3.860000 0 -8.754810e-01 -0.57313688
#> 5 5 5.5 4.500000e+00 1 4.360000 0 1.086611e+00 1.33082093
#> 6 6 1.0 1.200000e+00 2 1.138006 0 1.454260e+00 1.59215285
#> 7 7 2.0 2.100000e+00 2 2.125857 0 -4.143531e-01 -0.33525214
#> 8 8 3.0 NA 2 3.113707 1 NA NaN
#> 9 9 4.0 1.000000e+04 2 4.101558 1 1.272006e+05 NaN
#> 10 10 5.0 1.000000e+02 2 5.089408 1 1.226885e+03 NaN
#> 11 11 6.0 6.000000e+00 2 6.077259 0 -1.277875e+00 -0.58107071
#> 12 12 7.0 7.000000e+00 2 7.065109 0 -1.032417e+00 -0.53024374
#> 13 13 8.0 8.100000e+00 2 8.052960 0 7.308001e-01 0.45967977
#> 14 14 9.0 9.100000e+00 2 9.040810 0 1.089940e+00 0.88186791
#> 15 15 1.0 1.000001e+07 3 -77.248828 1 3.336155e+05 NaN
#> 16 16 2.0 1.000120e+05 3 -52.019348 1 3.403875e+03 NaN
#> 17 17 3.0 1.024687e+03 3 -26.789868 1 3.674080e+01 NaN
#> 18 18 4.0 2.824773e+01 3 -1.560388 0 1.755742e+00 0.92071906
#> 19 19 5.0 4.414688e+01 3 23.669092 0 1.154605e+00 0.53897962
#> 20 20 6.0 5.020195e+01 3 48.898572 0 2.413159e-01 0.10020097
#> 21 21 7.0 7.314708e+01 3 74.128052 0 8.408804e-02 0.03106598
#> 22 22 8.0 8.412607e+01 3 99.357532 0 -5.466308e-01 -0.18021884
#> 23 23 9.0 1.202427e+02 3 124.587012 0 -1.702079e-01 -0.05049181
#> 24 24 10.0 1.410798e+02 3 149.816492 0 -4.019105e-01 -0.10909793
#> 25 25 11.0 1.549065e+02 3 175.045972 0 -9.265007e-01 -0.23670988
#> 26 26 12.0 1.886235e+02 3 200.275452 0 -6.386104e-01 -0.15965260
#> 27 27 13.0 2.193324e+02 3 225.504932 0 -4.817567e-01 -0.12308309
#> 28 28 14.0 2.257846e+02 3 250.734412 0 -1.349776e+00 -0.36639449
#> 29 29 15.0 2.608230e+02 3 275.963892 0 -9.872032e-01 -0.29285180
#> 30 30 16.0 3.036370e+02 3 301.193372 0 -3.310073e-01 -0.10912988
#> 31 31 17.0 3.249530e+02 3 326.422852 0 -5.581320e-01 -0.20619956
#> 32 32 18.0 3.629252e+02 3 351.652332 0 -1.056216e-01 -0.04385700
#> 33 33 19.0 4.203940e+02 3 376.881812 0 1.224289e+00 0.57150868
#> 34 34 20.0 4.807166e+02 3 402.111292 1 3.648248e+00 1.91315754
#> hii leaveOutResid limLo limUp
#> 1 0.60000000 -1.500000e-01 -2.5 2.5
#> 2 0.30000000 3.428571e-01 -2.5 2.5
#> 3 0.20000000 -2.000000e-01 -2.5 2.5
#> 4 0.30000000 -2.285714e-01 -2.5 2.5
#> 5 0.60000000 3.500000e-01 -2.5 2.5
#> 6 0.54517134 1.363014e-01 -2.5 2.5
#> 7 0.39563863 -4.278351e-02 -2.5 2.5
#> 8 NaN NA -2.5 2.5
#> 9 NaN 9.995898e+03 -2.5 2.5
#> 10 NaN 9.491059e+01 -2.5 2.5
#> 11 0.17133956 -9.323308e-02 -2.5 2.5
#> 12 0.20872274 -8.228346e-02 -2.5 2.5
#> 13 0.28348910 6.565217e-02 -2.5 2.5
#> 14 0.39563863 9.793814e-02 -2.5 2.5
#> 15 NaN 1.000010e+07 -2.5 2.5
#> 16 NaN 1.000748e+05 -2.5 2.5
#> 17 NaN 1.060725e+03 -2.5 2.5
#> 18 0.21568627 4.783102e+01 -2.5 2.5
#> 19 0.17892157 3.244868e+01 -2.5 2.5
#> 20 0.14705882 6.949158e+00 -2.5 2.5
#> 21 0.12009804 2.388442e+00 -2.5 2.5
#> 22 0.09803922 -1.517825e+01 -2.5 2.5
#> 23 0.08088235 -4.726638e+00 -2.5 2.5
#> 24 0.06862745 -1.103529e+01 -2.5 2.5
#> 25 0.06127451 -2.473783e+01 -2.5 2.5
#> 26 0.05882353 -1.729308e+01 -2.5 2.5
#> 27 0.06127451 -1.314302e+01 -2.5 2.5
#> 28 0.06862745 -3.506242e+01 -2.5 2.5
#> 29 0.08088235 -2.653475e+01 -2.5 2.5
#> 30 0.09803922 -9.252479e+00 -2.5 2.5
#> 31 0.12009804 -1.568369e+01 -2.5 2.5
#> 32 0.14705882 -3.046685e+00 -2.5 2.5
#> 33 0.17892157 3.422256e+01 -2.5 2.5
#> 34 0.21568627 7.860534e+01 -2.5 2.5
#>
#> $aggregates
#> strata N coef coefB nModel sigmaHat
#> 1 1 5 1.8600000 0.4545455 5 0.20976177
#> 2 2 9 0.1501558 0.9878505 6 0.07147751
#> 3 3 20 -116.3498394 26.7707612 17 25.74693539
#>
#> $total
#> Ntotal
#> 1 34
#>
OutlierRegressionMicro(z,strataName="k")
#> id x y strata yHat outlier rStud dffits
#> 1 1 1.1 2.300000e+00 1 2.360000 0 -3.825460e-01 -0.46852129
#> 2 2 2.2 3.100000e+00 1 2.860000 0 1.819435e+00 1.19110000
#> 3 3 3.3 3.200000e+00 1 3.360000 0 -8.000000e-01 -0.40000000
#> 4 4 4.4 3.700000e+00 1 3.860000 0 -8.754810e-01 -0.57313688
#> 5 5 5.5 4.500000e+00 1 4.360000 0 1.086611e+00 1.33082093
#> 6 6 1.0 1.200000e+00 2 1.138006 0 1.454260e+00 1.59215285
#> 7 7 2.0 2.100000e+00 2 2.125857 0 -4.143531e-01 -0.33525214
#> 8 8 3.0 NA 2 3.113707 1 NA NaN
#> 9 9 4.0 1.000000e+04 2 4.101558 1 1.272006e+05 NaN
#> 10 10 5.0 1.000000e+02 2 5.089408 1 1.226885e+03 NaN
#> 11 11 6.0 6.000000e+00 2 6.077259 0 -1.277875e+00 -0.58107071
#> 12 12 7.0 7.000000e+00 2 7.065109 0 -1.032417e+00 -0.53024374
#> 13 13 8.0 8.100000e+00 2 8.052960 0 7.308001e-01 0.45967977
#> 14 14 9.0 9.100000e+00 2 9.040810 0 1.089940e+00 0.88186791
#> 15 15 1.0 1.000001e+07 3 -77.248828 1 3.336155e+05 NaN
#> 16 16 2.0 1.000120e+05 3 -52.019348 1 3.403875e+03 NaN
#> 17 17 3.0 1.024687e+03 3 -26.789868 1 3.674080e+01 NaN
#> 18 18 4.0 2.824773e+01 3 -1.560388 0 1.755742e+00 0.92071906
#> 19 19 5.0 4.414688e+01 3 23.669092 0 1.154605e+00 0.53897962
#> 20 20 6.0 5.020195e+01 3 48.898572 0 2.413159e-01 0.10020097
#> 21 21 7.0 7.314708e+01 3 74.128052 0 8.408804e-02 0.03106598
#> 22 22 8.0 8.412607e+01 3 99.357532 0 -5.466308e-01 -0.18021884
#> 23 23 9.0 1.202427e+02 3 124.587012 0 -1.702079e-01 -0.05049181
#> 24 24 10.0 1.410798e+02 3 149.816492 0 -4.019105e-01 -0.10909793
#> 25 25 11.0 1.549065e+02 3 175.045972 0 -9.265007e-01 -0.23670988
#> 26 26 12.0 1.886235e+02 3 200.275452 0 -6.386104e-01 -0.15965260
#> 27 27 13.0 2.193324e+02 3 225.504932 0 -4.817567e-01 -0.12308309
#> 28 28 14.0 2.257846e+02 3 250.734412 0 -1.349776e+00 -0.36639449
#> 29 29 15.0 2.608230e+02 3 275.963892 0 -9.872032e-01 -0.29285180
#> 30 30 16.0 3.036370e+02 3 301.193372 0 -3.310073e-01 -0.10912988
#> 31 31 17.0 3.249530e+02 3 326.422852 0 -5.581320e-01 -0.20619956
#> 32 32 18.0 3.629252e+02 3 351.652332 0 -1.056216e-01 -0.04385700
#> 33 33 19.0 4.203940e+02 3 376.881812 0 1.224289e+00 0.57150868
#> 34 34 20.0 4.807166e+02 3 402.111292 1 3.648248e+00 1.91315754
#> hii leaveOutResid limLo limUp
#> 1 0.60000000 -1.500000e-01 -2.5 2.5
#> 2 0.30000000 3.428571e-01 -2.5 2.5
#> 3 0.20000000 -2.000000e-01 -2.5 2.5
#> 4 0.30000000 -2.285714e-01 -2.5 2.5
#> 5 0.60000000 3.500000e-01 -2.5 2.5
#> 6 0.54517134 1.363014e-01 -2.5 2.5
#> 7 0.39563863 -4.278351e-02 -2.5 2.5
#> 8 NaN NA -2.5 2.5
#> 9 NaN 9.995898e+03 -2.5 2.5
#> 10 NaN 9.491059e+01 -2.5 2.5
#> 11 0.17133956 -9.323308e-02 -2.5 2.5
#> 12 0.20872274 -8.228346e-02 -2.5 2.5
#> 13 0.28348910 6.565217e-02 -2.5 2.5
#> 14 0.39563863 9.793814e-02 -2.5 2.5
#> 15 NaN 1.000010e+07 -2.5 2.5
#> 16 NaN 1.000748e+05 -2.5 2.5
#> 17 NaN 1.060725e+03 -2.5 2.5
#> 18 0.21568627 4.783102e+01 -2.5 2.5
#> 19 0.17892157 3.244868e+01 -2.5 2.5
#> 20 0.14705882 6.949158e+00 -2.5 2.5
#> 21 0.12009804 2.388442e+00 -2.5 2.5
#> 22 0.09803922 -1.517825e+01 -2.5 2.5
#> 23 0.08088235 -4.726638e+00 -2.5 2.5
#> 24 0.06862745 -1.103529e+01 -2.5 2.5
#> 25 0.06127451 -2.473783e+01 -2.5 2.5
#> 26 0.05882353 -1.729308e+01 -2.5 2.5
#> 27 0.06127451 -1.314302e+01 -2.5 2.5
#> 28 0.06862745 -3.506242e+01 -2.5 2.5
#> 29 0.08088235 -2.653475e+01 -2.5 2.5
#> 30 0.09803922 -9.252479e+00 -2.5 2.5
#> 31 0.12009804 -1.568369e+01 -2.5 2.5
#> 32 0.14705882 -3.046685e+00 -2.5 2.5
#> 33 0.17892157 3.422256e+01 -2.5 2.5
#> 34 0.21568627 7.860534e+01 -2.5 2.5
OutlierRegressionTall(z,strataName="k")
#> ID id x y strata yHat outlier rStud
#> 1 1 1 1.1 2.300000e+00 1 2.360000 0 -3.825460e-01
#> 2 2 2 2.2 3.100000e+00 1 2.860000 0 1.819435e+00
#> 3 3 3 3.3 3.200000e+00 1 3.360000 0 -8.000000e-01
#> 4 4 4 4.4 3.700000e+00 1 3.860000 0 -8.754810e-01
#> 5 5 5 5.5 4.500000e+00 1 4.360000 0 1.086611e+00
#> 6 6 6 1.0 1.200000e+00 2 1.138006 0 1.454260e+00
#> 7 7 7 2.0 2.100000e+00 2 2.125857 0 -4.143531e-01
#> 8 8 8 3.0 NA 2 3.113707 1 NA
#> 9 9 9 4.0 1.000000e+04 2 4.101558 1 1.272006e+05
#> 10 10 10 5.0 1.000000e+02 2 5.089408 1 1.226885e+03
#> 11 11 11 6.0 6.000000e+00 2 6.077259 0 -1.277875e+00
#> 12 12 12 7.0 7.000000e+00 2 7.065109 0 -1.032417e+00
#> 13 13 13 8.0 8.100000e+00 2 8.052960 0 7.308001e-01
#> 14 14 14 9.0 9.100000e+00 2 9.040810 0 1.089940e+00
#> 15 15 15 1.0 1.000001e+07 3 -77.248828 1 3.336155e+05
#> 16 16 16 2.0 1.000120e+05 3 -52.019348 1 3.403875e+03
#> 17 17 17 3.0 1.024687e+03 3 -26.789868 1 3.674080e+01
#> 18 18 18 4.0 2.824773e+01 3 -1.560388 0 1.755742e+00
#> 19 19 19 5.0 4.414688e+01 3 23.669092 0 1.154605e+00
#> 20 20 20 6.0 5.020195e+01 3 48.898572 0 2.413159e-01
#> 21 21 21 7.0 7.314708e+01 3 74.128052 0 8.408804e-02
#> 22 22 22 8.0 8.412607e+01 3 99.357532 0 -5.466308e-01
#> 23 23 23 9.0 1.202427e+02 3 124.587012 0 -1.702079e-01
#> 24 24 24 10.0 1.410798e+02 3 149.816492 0 -4.019105e-01
#> 25 25 25 11.0 1.549065e+02 3 175.045972 0 -9.265007e-01
#> 26 26 26 12.0 1.886235e+02 3 200.275452 0 -6.386104e-01
#> 27 27 27 13.0 2.193324e+02 3 225.504932 0 -4.817567e-01
#> 28 28 28 14.0 2.257846e+02 3 250.734412 0 -1.349776e+00
#> 29 29 29 15.0 2.608230e+02 3 275.963892 0 -9.872032e-01
#> 30 30 30 16.0 3.036370e+02 3 301.193372 0 -3.310073e-01
#> 31 31 31 17.0 3.249530e+02 3 326.422852 0 -5.581320e-01
#> 32 32 32 18.0 3.629252e+02 3 351.652332 0 -1.056216e-01
#> 33 33 33 19.0 4.203940e+02 3 376.881812 0 1.224289e+00
#> 34 34 34 20.0 4.807166e+02 3 402.111292 1 3.648248e+00
#> 35 1 NA NA NA 1 NA NA NA
#> 36 2 NA NA NA 2 NA NA NA
#> 37 3 NA NA NA 3 NA NA NA
#> 38 Total NA NA NA NA NA NA NA
#> dffits hii leaveOutResid limLo limUp N coef coefB
#> 1 -0.46852129 0.60000000 -1.500000e-01 -2.5 2.5 NA NA NA
#> 2 1.19110000 0.30000000 3.428571e-01 -2.5 2.5 NA NA NA
#> 3 -0.40000000 0.20000000 -2.000000e-01 -2.5 2.5 NA NA NA
#> 4 -0.57313688 0.30000000 -2.285714e-01 -2.5 2.5 NA NA NA
#> 5 1.33082093 0.60000000 3.500000e-01 -2.5 2.5 NA NA NA
#> 6 1.59215285 0.54517134 1.363014e-01 -2.5 2.5 NA NA NA
#> 7 -0.33525214 0.39563863 -4.278351e-02 -2.5 2.5 NA NA NA
#> 8 NaN NaN NA -2.5 2.5 NA NA NA
#> 9 NaN NaN 9.995898e+03 -2.5 2.5 NA NA NA
#> 10 NaN NaN 9.491059e+01 -2.5 2.5 NA NA NA
#> 11 -0.58107071 0.17133956 -9.323308e-02 -2.5 2.5 NA NA NA
#> 12 -0.53024374 0.20872274 -8.228346e-02 -2.5 2.5 NA NA NA
#> 13 0.45967977 0.28348910 6.565217e-02 -2.5 2.5 NA NA NA
#> 14 0.88186791 0.39563863 9.793814e-02 -2.5 2.5 NA NA NA
#> 15 NaN NaN 1.000010e+07 -2.5 2.5 NA NA NA
#> 16 NaN NaN 1.000748e+05 -2.5 2.5 NA NA NA
#> 17 NaN NaN 1.060725e+03 -2.5 2.5 NA NA NA
#> 18 0.92071906 0.21568627 4.783102e+01 -2.5 2.5 NA NA NA
#> 19 0.53897962 0.17892157 3.244868e+01 -2.5 2.5 NA NA NA
#> 20 0.10020097 0.14705882 6.949158e+00 -2.5 2.5 NA NA NA
#> 21 0.03106598 0.12009804 2.388442e+00 -2.5 2.5 NA NA NA
#> 22 -0.18021884 0.09803922 -1.517825e+01 -2.5 2.5 NA NA NA
#> 23 -0.05049181 0.08088235 -4.726638e+00 -2.5 2.5 NA NA NA
#> 24 -0.10909793 0.06862745 -1.103529e+01 -2.5 2.5 NA NA NA
#> 25 -0.23670988 0.06127451 -2.473783e+01 -2.5 2.5 NA NA NA
#> 26 -0.15965260 0.05882353 -1.729308e+01 -2.5 2.5 NA NA NA
#> 27 -0.12308309 0.06127451 -1.314302e+01 -2.5 2.5 NA NA NA
#> 28 -0.36639449 0.06862745 -3.506242e+01 -2.5 2.5 NA NA NA
#> 29 -0.29285180 0.08088235 -2.653475e+01 -2.5 2.5 NA NA NA
#> 30 -0.10912988 0.09803922 -9.252479e+00 -2.5 2.5 NA NA NA
#> 31 -0.20619956 0.12009804 -1.568369e+01 -2.5 2.5 NA NA NA
#> 32 -0.04385700 0.14705882 -3.046685e+00 -2.5 2.5 NA NA NA
#> 33 0.57150868 0.17892157 3.422256e+01 -2.5 2.5 NA NA NA
#> 34 1.91315754 0.21568627 7.860534e+01 -2.5 2.5 NA NA NA
#> 35 NA NA NA NA NA 5 1.8600000 0.4545455
#> 36 NA NA NA NA NA 9 0.1501558 0.9878505
#> 37 NA NA NA NA NA 20 -116.3498394 26.7707612
#> 38 NA NA NA NA NA NA NA NA
#> nModel sigmaHat Ntotal
#> 1 NA NA NA
#> 2 NA NA NA
#> 3 NA NA NA
#> 4 NA NA NA
#> 5 NA NA NA
#> 6 NA NA NA
#> 7 NA NA NA
#> 8 NA NA NA
#> 9 NA NA NA
#> 10 NA NA NA
#> 11 NA NA NA
#> 12 NA NA NA
#> 13 NA NA NA
#> 14 NA NA NA
#> 15 NA NA NA
#> 16 NA NA NA
#> 17 NA NA NA
#> 18 NA NA NA
#> 19 NA NA NA
#> 20 NA NA NA
#> 21 NA NA NA
#> 22 NA NA NA
#> 23 NA NA NA
#> 24 NA NA NA
#> 25 NA NA NA
#> 26 NA NA NA
#> 27 NA NA NA
#> 28 NA NA NA
#> 29 NA NA NA
#> 30 NA NA NA
#> 31 NA NA NA
#> 32 NA NA NA
#> 33 NA NA NA
#> 34 NA NA NA
#> 35 5 0.20976177 NA
#> 36 6 0.07147751 NA
#> 37 17 25.74693539 NA
#> 38 NA NA 34
OutlierRegressionWide(z,strataName="k")
#> id x y strata yHat outlier rStud dffits
#> 1 1 1.1 2.300000e+00 1 2.360000 0 -3.825460e-01 -0.46852129
#> 2 2 2.2 3.100000e+00 1 2.860000 0 1.819435e+00 1.19110000
#> 3 3 3.3 3.200000e+00 1 3.360000 0 -8.000000e-01 -0.40000000
#> 4 4 4.4 3.700000e+00 1 3.860000 0 -8.754810e-01 -0.57313688
#> 5 5 5.5 4.500000e+00 1 4.360000 0 1.086611e+00 1.33082093
#> 6 6 1.0 1.200000e+00 2 1.138006 0 1.454260e+00 1.59215285
#> 7 7 2.0 2.100000e+00 2 2.125857 0 -4.143531e-01 -0.33525214
#> 8 8 3.0 NA 2 3.113707 1 NA NaN
#> 9 9 4.0 1.000000e+04 2 4.101558 1 1.272006e+05 NaN
#> 10 10 5.0 1.000000e+02 2 5.089408 1 1.226885e+03 NaN
#> 11 11 6.0 6.000000e+00 2 6.077259 0 -1.277875e+00 -0.58107071
#> 12 12 7.0 7.000000e+00 2 7.065109 0 -1.032417e+00 -0.53024374
#> 13 13 8.0 8.100000e+00 2 8.052960 0 7.308001e-01 0.45967977
#> 14 14 9.0 9.100000e+00 2 9.040810 0 1.089940e+00 0.88186791
#> 15 15 1.0 1.000001e+07 3 -77.248828 1 3.336155e+05 NaN
#> 16 16 2.0 1.000120e+05 3 -52.019348 1 3.403875e+03 NaN
#> 17 17 3.0 1.024687e+03 3 -26.789868 1 3.674080e+01 NaN
#> 18 18 4.0 2.824773e+01 3 -1.560388 0 1.755742e+00 0.92071906
#> 19 19 5.0 4.414688e+01 3 23.669092 0 1.154605e+00 0.53897962
#> 20 20 6.0 5.020195e+01 3 48.898572 0 2.413159e-01 0.10020097
#> 21 21 7.0 7.314708e+01 3 74.128052 0 8.408804e-02 0.03106598
#> 22 22 8.0 8.412607e+01 3 99.357532 0 -5.466308e-01 -0.18021884
#> 23 23 9.0 1.202427e+02 3 124.587012 0 -1.702079e-01 -0.05049181
#> 24 24 10.0 1.410798e+02 3 149.816492 0 -4.019105e-01 -0.10909793
#> 25 25 11.0 1.549065e+02 3 175.045972 0 -9.265007e-01 -0.23670988
#> 26 26 12.0 1.886235e+02 3 200.275452 0 -6.386104e-01 -0.15965260
#> 27 27 13.0 2.193324e+02 3 225.504932 0 -4.817567e-01 -0.12308309
#> 28 28 14.0 2.257846e+02 3 250.734412 0 -1.349776e+00 -0.36639449
#> 29 29 15.0 2.608230e+02 3 275.963892 0 -9.872032e-01 -0.29285180
#> 30 30 16.0 3.036370e+02 3 301.193372 0 -3.310073e-01 -0.10912988
#> 31 31 17.0 3.249530e+02 3 326.422852 0 -5.581320e-01 -0.20619956
#> 32 32 18.0 3.629252e+02 3 351.652332 0 -1.056216e-01 -0.04385700
#> 33 33 19.0 4.203940e+02 3 376.881812 0 1.224289e+00 0.57150868
#> 34 34 20.0 4.807166e+02 3 402.111292 1 3.648248e+00 1.91315754
#> hii leaveOutResid limLo limUp Strata_N Strata_coef Strata_coefB
#> 1 0.60000000 -1.500000e-01 -2.5 2.5 5 1.8600000 0.4545455
#> 2 0.30000000 3.428571e-01 -2.5 2.5 5 1.8600000 0.4545455
#> 3 0.20000000 -2.000000e-01 -2.5 2.5 5 1.8600000 0.4545455
#> 4 0.30000000 -2.285714e-01 -2.5 2.5 5 1.8600000 0.4545455
#> 5 0.60000000 3.500000e-01 -2.5 2.5 5 1.8600000 0.4545455
#> 6 0.54517134 1.363014e-01 -2.5 2.5 9 0.1501558 0.9878505
#> 7 0.39563863 -4.278351e-02 -2.5 2.5 9 0.1501558 0.9878505
#> 8 NaN NA -2.5 2.5 9 0.1501558 0.9878505
#> 9 NaN 9.995898e+03 -2.5 2.5 9 0.1501558 0.9878505
#> 10 NaN 9.491059e+01 -2.5 2.5 9 0.1501558 0.9878505
#> 11 0.17133956 -9.323308e-02 -2.5 2.5 9 0.1501558 0.9878505
#> 12 0.20872274 -8.228346e-02 -2.5 2.5 9 0.1501558 0.9878505
#> 13 0.28348910 6.565217e-02 -2.5 2.5 9 0.1501558 0.9878505
#> 14 0.39563863 9.793814e-02 -2.5 2.5 9 0.1501558 0.9878505
#> 15 NaN 1.000010e+07 -2.5 2.5 20 -116.3498394 26.7707612
#> 16 NaN 1.000748e+05 -2.5 2.5 20 -116.3498394 26.7707612
#> 17 NaN 1.060725e+03 -2.5 2.5 20 -116.3498394 26.7707612
#> 18 0.21568627 4.783102e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 19 0.17892157 3.244868e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 20 0.14705882 6.949158e+00 -2.5 2.5 20 -116.3498394 26.7707612
#> 21 0.12009804 2.388442e+00 -2.5 2.5 20 -116.3498394 26.7707612
#> 22 0.09803922 -1.517825e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 23 0.08088235 -4.726638e+00 -2.5 2.5 20 -116.3498394 26.7707612
#> 24 0.06862745 -1.103529e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 25 0.06127451 -2.473783e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 26 0.05882353 -1.729308e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 27 0.06127451 -1.314302e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 28 0.06862745 -3.506242e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 29 0.08088235 -2.653475e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 30 0.09803922 -9.252479e+00 -2.5 2.5 20 -116.3498394 26.7707612
#> 31 0.12009804 -1.568369e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 32 0.14705882 -3.046685e+00 -2.5 2.5 20 -116.3498394 26.7707612
#> 33 0.17892157 3.422256e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> 34 0.21568627 7.860534e+01 -2.5 2.5 20 -116.3498394 26.7707612
#> Strata_nModel Strata_sigmaHat Total_Ntotal
#> 1 5 0.20976177 34
#> 2 5 0.20976177 34
#> 3 5 0.20976177 34
#> 4 5 0.20976177 34
#> 5 5 0.20976177 34
#> 6 6 0.07147751 34
#> 7 6 0.07147751 34
#> 8 6 0.07147751 34
#> 9 6 0.07147751 34
#> 10 6 0.07147751 34
#> 11 6 0.07147751 34
#> 12 6 0.07147751 34
#> 13 6 0.07147751 34
#> 14 6 0.07147751 34
#> 15 17 25.74693539 34
#> 16 17 25.74693539 34
#> 17 17 25.74693539 34
#> 18 17 25.74693539 34
#> 19 17 25.74693539 34
#> 20 17 25.74693539 34
#> 21 17 25.74693539 34
#> 22 17 25.74693539 34
#> 23 17 25.74693539 34
#> 24 17 25.74693539 34
#> 25 17 25.74693539 34
#> 26 17 25.74693539 34
#> 27 17 25.74693539 34
#> 28 17 25.74693539 34
#> 29 17 25.74693539 34
#> 30 17 25.74693539 34
#> 31 17 25.74693539 34
#> 32 17 25.74693539 34
#> 33 17 25.74693539 34
#> 34 17 25.74693539 34
rateData <- KostraData("rateData") # Real Kostra data set
w <- rateData$data[, c(17,19,16,5)] # Data with id, strata, x and y
w <- w[is.finite(w[,"Ny.kostragruppe"]), ] # Remove Longyearbyen
w[w[,"Ny.kostragruppe"]>13,"Ny.kostragruppe"]=13 # Combine small strata
OutlierRegression(w, strataName = names(w)[2], method="ratio")
#> $micro
#> id x y strata yHat outlier rStud dffits
#> 1 101 30544 2792 13 18508.52576 0 -1.714493e+00 -1.684697e-01
#> 2 104 32182 11319 13 19501.09272 0 -9.043951e-01 -9.124317e-02
#> 3 105 54678 32854 13 33132.83040 0 -1.479120e-01 -1.952072e-02
#> 4 106 78967 42362 13 47851.05926 0 -4.998320e-01 -7.958289e-02
#> 5 111 4511 3278 3 2586.87759 0 3.295957e-03 6.763138e-04
#> 6 118 1404 853 5 412.01137 0 7.102244e-01 1.291956e-01
#> 7 119 3610 1531 1 934.16598 0 3.970479e-01 9.134040e-02
#> 8 121 672 103 4 209.27495 0 -3.264588e-01 -6.486459e-02
#> 9 122 5343 2226 10 1386.87240 0 3.677956e-01 6.189043e-02
#> 10 123 5736 2512 11 2829.39052 0 -1.604724e-01 -1.871488e-02
#> 11 124 15615 6721 8 6968.96516 0 -2.251146e-01 -5.281668e-02
#> 12 125 11396 10538 10 2958.03815 1 3.853000e+00 9.624534e-01
#> 13 127 3742 0 2 1133.05863 0 -1.086607e+00 -1.594188e-01
#> 14 128 8084 474 11 3987.58594 0 -1.167086e+00 -1.620356e-01
#> 15 135 7357 1507 7 2349.96334 0 -3.778099e-01 -5.227807e-02
#> 16 136 15458 5491 7 4937.57420 0 1.726162e-01 3.499300e-02
#> 17 137 5186 331 1 1341.99025 0 -8.603773e-01 -2.400200e-01
#> 18 138 5382 811 1 1392.70951 0 -5.396811e-01 -1.535999e-01
#> 19 211 16732 9867 7 5344.51361 0 1.402720e+00 2.963497e-01
#> 20 213 30261 22914 13 18337.03831 0 3.685190e-01 3.604170e-02
#> 21 214 18992 9635 7 6066.39987 0 1.026572e+00 2.317647e-01
#> 22 215 15695 7751 8 7004.66911 0 -2.946119e-02 -6.930882e-03
#> 23 216 18623 10648 7 5948.53437 0 1.383956e+00 3.092466e-01
#> 24 217 26792 14146 13 16234.95358 0 -3.126921e-01 -2.875976e-02
#> 25 219 122348 97383 13 74138.32865 0 1.000957e+00 1.997708e-01
#> 26 220 60106 53067 13 36421.99612 0 1.075197e+00 1.489048e-01
#> 27 221 15914 0 7 5083.22912 0 -1.633022e+00 -3.360997e-01
#> 28 226 17443 4400 7 5571.62031 0 -3.454561e-01 -7.458910e-02
#> 29 227 11374 1353 7 3633.06824 0 -8.340055e-01 -1.442459e-01
#> 30 228 17426 11010 7 5566.19019 0 1.678631e+00 3.622563e-01
#> 31 229 10870 2809 7 3472.08122 0 -2.452704e-01 -4.144291e-02
#> 32 230 36368 23871 13 22037.65273 0 6.585325e-02 7.067409e-03
#> 33 231 52522 41227 13 31826.37475 0 6.004956e-01 7.764571e-02
#> 34 233 22857 9878 13 13850.49022 0 -5.439004e-01 -4.617694e-02
#> 35 234 6323 400 7 2019.68441 0 -7.883861e-01 -1.009980e-01
#> 36 235 34189 23717 13 20717.25993 0 1.851816e-01 1.926258e-02
#> 37 236 20783 112 7 6638.47875 0 -1.870855e+00 -4.429077e-01
#> 38 237 23811 13445 13 14428.57867 0 -1.952079e-01 -1.691794e-02
#> 39 238 12267 4830 7 3918.30914 0 3.182563e-01 5.723144e-02
#> 40 239 2837 1245 2 859.02922 0 2.589437e-01 3.299307e-02
#> 41 301 658390 455113 13 398959.80481 0 8.733840e-01 4.450519e-01
#> 42 402 17835 10354 8 7959.74983 0 2.554920e-01 6.431560e-02
#> 43 403 30120 23153 13 18251.59757 0 4.027705e-01 3.929879e-02
#> 44 412 33597 7146 13 20358.52999 0 -1.387563e+00 -1.430658e-01
#> 45 415 7588 3649 7 2423.74906 0 5.422901e-01 7.622928e-02
#> 46 417 20119 616 10 5222.25075 0 -1.824118e+00 -6.204226e-01
#> 47 418 5131 2657 10 1331.84396 0 6.748081e-01 1.112146e-01
#> 48 419 7901 2904 7 2523.72711 0 1.642528e-01 2.356987e-02
#> 49 420 6142 1440 11 3029.65770 0 -6.166337e-01 -7.445152e-02
#> 50 423 4763 1537 2 1442.21226 0 -7.386128e-02 -1.226172e-02
#> 51 425 7456 1500 11 3677.81306 0 -7.631385e-01 -1.016778e-01
#> 52 426 3760 NA 2 1138.50894 1 NA NaN
#> 53 427 21030 7919 13 12743.39631 0 -6.641352e-01 -5.406886e-02
#> 54 428 6525 10 11 3218.57969 0 -1.178312e+00 -1.467031e-01
#> 55 429 4429 0 2 1341.07875 0 -1.187036e+00 -1.898417e-01
#> 56 430 2600 309 2 787.26682 0 -5.858283e-01 -7.140858e-02
#> 57 432 1881 742 3 1078.67806 0 -3.029414e-01 -3.965675e-02
#> 58 434 1305 409 6 681.48091 0 -4.454440e-01 -6.490330e-02
#> 59 436 1620 569 5 475.39774 0 8.400485e-02 1.645655e-02
#> 60 437 5580 1909 12 4615.89146 0 -6.832261e-01 -1.259368e-01
#> 61 438 2426 830 2 734.58050 0 -3.611682e-03 -4.250426e-04
#> 62 439 1592 0 2 482.04953 0 -6.998152e-01 -6.655812e-02
#> 63 441 1956 1828 5 573.99875 0 1.886441e+00 4.076991e-01
#> 64 501 27476 20635 13 16649.43210 0 3.328854e-01 3.100875e-02
#> 65 502 30137 7666 13 18261.89893 0 -1.179243e+00 -1.150929e-01
#> 66 511 2701 1256 2 817.84911 0 3.220455e-01 4.002195e-02
#> 67 512 2055 742 5 603.05084 0 1.244378e-01 2.759844e-02
#> 68 513 2204 3199 3 1263.90561 0 7.290432e-01 1.034578e-01
#> 69 514 2347 NA 3 1345.91037 1 NA NaN
#> 70 515 3664 1721 2 1109.44063 0 3.908405e-01 5.672769e-02
#> 71 516 5741 7149 12 4749.07399 0 5.955657e-01 1.114057e-01
#> 72 517 5935 4099 11 2927.55103 0 3.844305e-01 4.561555e-02
#> 73 519 3154 0 2 955.01521 0 -9.941022e-01 -1.336730e-01
#> 74 520 4462 1576 2 1351.07098 0 3.298380e-02 5.295194e-03
#> 75 521 5072 1535 11 2501.85995 0 -4.219697e-01 -4.623933e-02
#> 76 522 6227 5721 11 3071.58556 0 9.065372e-01 1.102200e-01
#> 77 528 14906 824 10 3869.12221 0 -1.357205e+00 -3.915113e-01
#> 78 529 13180 1803 7 4209.93841 0 -8.194891e-01 -1.529371e-01
#> 79 532 6629 3715 7 2117.42653 0 7.591856e-01 9.962237e-02
#> 80 533 9044 1433 7 2888.82268 0 -5.918886e-01 -9.100633e-02
#> 81 534 13695 3384 10 3554.78523 0 -2.626321e-01 -7.237423e-02
#> 82 536 5758 1961 10 1494.59316 0 1.354426e-01 2.368611e-02
#> 83 538 6751 445 11 3330.05847 0 -1.045084e+00 -1.323856e-01
#> 84 540 3058 0 2 925.94690 0 -9.782991e-01 -1.294950e-01
#> 85 541 1321 1097 6 689.83623 0 4.898888e-01 7.182470e-02
#> 86 542 6458 5303 11 3185.53068 0 6.989019e-01 8.656045e-02
#> 87 543 2168 801 2 656.45941 0 6.137533e-02 6.823095e-03
#> 88 544 3220 0 2 974.99968 0 -1.004843e+00 -1.365496e-01
#> 89 545 1590 140 6 830.31008 0 -9.509639e-01 -1.532993e-01
#> 90 602 67895 56116 13 41141.83986 0 8.793455e-01 1.295928e-01
#> 91 604 27013 0 13 16368.87135 0 -1.891059e+00 -1.746516e-01
#> 92 605 29801 15997 13 18058.29545 0 -3.032229e-01 -2.942725e-02
#> 93 612 6767 2624 8 3020.10805 0 -2.312626e-01 -3.517467e-02
#> 94 615 1074 1145 5 315.17109 0 1.659478e+00 2.630025e-01
#> 95 616 3422 1726 2 1036.16426 0 4.815847e-01 6.750384e-02
#> 96 617 4578 2957 2 1386.19520 0 1.059659e+00 1.723716e-01
#> 97 618 2422 1291 2 733.36932 0 4.759367e-01 5.596402e-02
#> 98 619 4711 690 3 2701.56957 0 -8.599830e-01 -1.805022e-01
#> 99 620 4497 1208 3 2578.84915 0 -6.586556e-01 -1.349341e-01
#> 100 621 3512 106 2 1063.41580 0 -9.571820e-01 -1.359565e-01
#> 101 622 2275 260 1 588.70571 0 -4.291192e-01 -7.761154e-02
#> 102 623 13794 3835 10 3580.48247 0 -1.052981e-01 -2.912996e-02
#> 103 624 18205 7781 7 5815.01735 0 5.699950e-01 1.258580e-01
#> 104 625 24431 5406 13 14804.27557 0 -1.152020e+00 -1.011427e-01
#> 105 626 25731 20942 13 15592.02712 0 4.997733e-01 4.503959e-02
#> 106 627 21492 4783 13 13023.35109 0 -1.075198e+00 -8.849723e-02
#> 107 628 9413 16 7 3006.68818 0 -1.215077e+00 -1.906904e-01
#> 108 631 2699 1216 1 698.42493 0 4.102393e-01 8.106331e-02
#> 109 632 1404 304 6 733.17946 0 -6.455453e-01 -9.764021e-02
#> 110 633 2548 1873 6 1330.58495 0 4.442538e-01 9.137666e-02
#> 111 701 27178 2934 13 16468.85520 0 -1.561093e+00 -1.446205e-01
#> 112 702 10741 2043 7 3430.87621 0 -5.182025e-01 -8.702392e-02
#> 113 704 42276 29885 13 25617.68057 0 2.540211e-01 2.942028e-02
#> 114 706 45820 20503 13 27765.21250 0 -7.163561e-01 -8.642329e-02
#> 115 709 43867 14068 13 26581.76728 0 -1.178483e+00 -1.390695e-01
#> 116 711 6604 781 7 2109.44107 0 -6.305497e-01 -8.258356e-02
#> 117 713 9297 2501 10 2413.20469 0 -1.227137e-01 -2.752881e-02
#> 118 714 3163 2201 2 957.74037 0 1.021357e+00 1.375372e-01
#> 119 716 9361 3876 8 4177.80870 0 -2.110362e-01 -3.792093e-02
#> 120 719 5937 1232 10 1541.05585 0 -2.995369e-01 -5.321608e-02
#> 121 720 11657 2907 7 3723.46373 0 -2.920612e-01 -5.115721e-02
#> 122 722 21621 7164 13 13101.52028 0 -7.917125e-01 -6.536073e-02
#> 123 723 4971 1143 1 1286.35432 0 -2.288851e-01 -6.241403e-02
#> 124 728 2474 0 1 640.20129 0 -7.407199e-01 -1.399052e-01
#> 125 805 35955 12781 13 21787.39012 0 -9.444898e-01 -1.007794e-01
#> 126 806 53952 72675 13 32692.90146 1 3.138297e+00 4.113711e-01
#> 127 807 12717 9812 11 6272.90084 0 8.305680e-01 1.454368e-01
#> 128 811 2335 106 1 604.23201 0 -6.048821e-01 -1.108815e-01
#> 129 814 14088 6103 8 6287.46597 0 -2.050667e-01 -4.557748e-02
#> 130 815 10607 4926 11 5232.10342 0 -1.424123e-01 -2.271688e-02
#> 131 817 4136 1600 2 1252.35984 0 1.424934e-01 2.200356e-02
#> 132 819 6534 2033 11 3223.01911 0 -4.605693e-01 -5.738231e-02
#> 133 821 6101 265 11 3009.43367 0 -1.042560e+00 -1.254504e-01
#> 134 822 4338 447 1 1122.55181 0 -6.430796e-01 -1.630444e-01
#> 135 826 5940 3801 12 4913.69091 0 -2.694086e-01 -5.129232e-02
#> 136 827 1613 0 5 473.34355 0 -8.483670e-01 -1.658219e-01
#> 137 828 2991 1015 2 905.65964 0 -1.176064e-02 -1.539282e-03
#> 138 829 2448 2806 2 741.24199 0 2.107499e+00 2.491598e-01
#> 139 830 1443 377 5 423.45613 0 -1.440006e-01 -2.656843e-02
#> 140 831 1323 1587 6 690.88065 0 1.177992e+00 1.728439e-01
#> 141 833 2246 2287 3 1287.99093 0 2.953535e-01 4.231889e-02
#> 142 834 3727 0 3 2137.28503 0 -9.571308e-01 -1.778681e-01
#> 143 901 6920 2037 11 3413.42092 0 -5.138039e-01 -6.590876e-02
#> 144 904 22550 8696 13 13664.45966 0 -6.638880e-01 -5.598133e-02
#> 145 906 44313 23978 13 26852.02666 0 -3.547167e-01 -4.207436e-02
#> 146 911 2473 0 2 748.81187 0 -8.767270e-01 -1.041867e-01
#> 147 912 2036 2438 1 526.85926 0 2.298479e+00 3.925927e-01
#> 148 914 6014 370 10 1561.04260 0 -7.957277e-01 -1.423129e-01
#> 149 919 5618 11348 11 2771.18478 1 3.540664e+00 4.085988e-01
#> 150 926 10577 4156 11 5217.30535 0 -3.503364e-01 -5.580277e-02
#> 151 928 5147 387 2 1558.48551 0 -9.977856e-01 -1.723819e-01
#> 152 929 1847 1072 6 964.51743 0 4.273719e-02 7.440993e-03
#> 153 935 1317 NA 5 386.48075 1 NA NaN
#> 154 937 3582 1088 1 926.92037 0 3.064960e-02 7.022066e-03
#> 155 938 1204 784 6 628.73795 0 1.564817e-01 2.188209e-02
#> 156 940 1242 3053 6 648.58183 1 3.951750e+00 5.614308e-01
#> 157 941 945 4103 13 572.63478 0 2.060479e+00 3.544744e-02
#> 158 1001 88447 78937 13 53595.58598 0 1.369225e+00 2.310740e-01
#> 159 1002 15529 14448 8 6930.58341 0 1.369268e+00 3.203250e-01
#> 160 1003 9705 11708 11 4787.17485 0 2.001566e+00 3.050726e-01
#> 161 1004 9096 6981 11 4486.77408 0 6.868735e-01 1.012794e-01
#> 162 1014 14308 6404 8 6385.65184 0 -1.643327e-01 -3.682235e-02
#> 163 1017 6419 3191 10 1666.16768 0 6.860515e-01 1.268985e-01
#> 164 1018 11260 1007 7 3596.65451 0 -9.553606e-01 -1.643801e-01
#> 165 1021 2290 1879 4 713.15422 0 1.865307e+00 7.192028e-01
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#> 413 2011 2956 1708 3 1695.14745 0 -1.693739e-01 -2.793187e-02
#> 414 2012 20097 14343 12 16624.65423 0 -3.144622e-01 -1.152130e-01
#> 415 2014 951 0 6 496.61942 0 -8.662787e-01 -1.074408e-01
#> 416 2015 1054 24 6 550.40681 0 -8.758543e-01 -1.144552e-01
#> 417 2017 1035 530 6 540.48486 0 -7.738804e-02 -1.001984e-02
#> 418 2018 1215 653 6 634.48223 0 -3.998030e-02 -5.616747e-03
#> 419 2019 3276 2742 3 1878.65462 0 1.371894e-01 2.385250e-02
#> 420 2020 3978 0 3 2281.22346 0 -9.910445e-01 -1.904926e-01
#> 421 2021 2668 4038 3 1529.99100 0 8.757760e-01 1.370290e-01
#> 422 2022 1318 1667 6 688.26961 0 1.300758e+00 1.904884e-01
#> 423 2023 1139 1569 6 594.79445 0 1.405720e+00 1.910924e-01
#> 424 2024 1000 1048 6 522.20760 0 7.713462e-01 9.813930e-02
#> 425 2025 2922 NA 6 1525.89060 1 NA NaN
#> 426 2027 959 NA 13 581.11826 1 NA NaN
#> 427 2028 2211 NA 3 1267.91983 1 NA NaN
#> 428 2030 10227 19083 12 8459.98601 0 2.260494e+00 5.722442e-01
#> hii leaveOutResid limLo limUp
#> 1 0.0095631071 -1.681718e+04 -2.5 2.5
#> 2 0.0100759532 -9.265686e+03 -2.5 2.5
#> 3 0.0171192893 -1.995419e+03 -2.5 2.5
#> 4 0.0247240009 -8.119603e+03 -2.5 2.5
#> 5 0.0404037690 1.078077e+01 -2.5 2.5
#> 6 0.0320306618 4.180575e+02 -2.5 2.5
#> 7 0.0502624507 4.961012e+02 -2.5 2.5
#> 8 0.0379789759 -1.302379e+02 -2.5 2.5
#> 9 0.0275364111 6.482532e+02 -2.5 2.5
#> 10 0.0134185797 -4.383614e+02 -2.5 2.5
#> 11 0.0521750462 -1.202099e+03 -2.5 2.5
#> 12 0.0587319748 7.579962e+03 -2.5 2.5
#> 13 0.0210710063 -1.313299e+03 -2.5 2.5
#> 14 0.0189114013 -3.746640e+03 -2.5 2.5
#> 15 0.0187869316 -8.591033e+02 -2.5 2.5
#> 16 0.0394737514 5.761694e+02 -2.5 2.5
#> 17 0.0722052824 -1.284250e+03 -2.5 2.5
#> 18 0.0749342133 -8.313601e+02 -2.5 2.5
#> 19 0.0427270545 4.724344e+03 -2.5 2.5
#> 20 0.0094745019 3.680711e+03 -2.5 2.5
#> 21 0.0484982201 3.750492e+03 -2.5 2.5
#> 22 0.0524423535 -1.579327e+02 -2.5 2.5
#> 23 0.0475559369 4.934112e+03 -2.5 2.5
#> 24 0.0083883829 -2.937982e+03 -2.5 2.5
#> 25 0.0383062805 2.025598e+04 -2.5 2.5
#> 26 0.0188187571 1.507933e+04 -2.5 2.5
#> 27 0.0406381990 -5.298553e+03 -2.5 2.5
#> 28 0.0445426734 -1.226240e+03 -2.5 2.5
#> 29 0.0290447955 -2.348273e+03 -2.5 2.5
#> 30 0.0444992620 5.697337e+03 -2.5 2.5
#> 31 0.0277577745 -6.820124e+02 -2.5 2.5
#> 32 0.0113865597 7.225401e+02 -2.5 2.5
#> 33 0.0164442612 7.914687e+03 -2.5 2.5
#> 34 0.0071563626 -4.709497e+03 -2.5 2.5
#> 35 0.0161464957 -1.646266e+03 -2.5 2.5
#> 36 0.0107043305 1.968828e+03 -2.5 2.5
#> 37 0.0530717412 -6.892263e+03 -2.5 2.5
#> 38 0.0074550532 -1.729128e+03 -2.5 2.5
#> 39 0.0313251720 9.411733e+02 -2.5 2.5
#> 40 0.0159749986 2.746896e+02 -2.5 2.5
#> 41 0.2061371829 4.521524e+04 -2.5 2.5
#> 42 0.0595928241 1.463305e+03 -2.5 2.5
#> 43 0.0094303558 4.012456e+03 -2.5 2.5
#> 44 0.0105189795 -1.439775e+04 -2.5 2.5
#> 45 0.0193768163 1.249462e+03 -2.5 2.5
#> 46 0.1036880134 -6.015988e+03 -2.5 2.5
#> 47 0.0264438191 1.155262e+03 -2.5 2.5
#> 48 0.0201760972 3.881033e+02 -2.5 2.5
#> 49 0.0143683606 -1.737863e+03 -2.5 2.5
#> 50 0.0268202038 -1.021475e+02 -2.5 2.5
#> 51 0.0174422821 -2.368728e+03 -2.5 2.5
#> 52 NaN NA -2.5 2.5
#> 53 0.0065843420 -5.507749e+03 -2.5 2.5
#> 54 0.0152643362 -3.391264e+03 -2.5 2.5
#> 55 0.0249394673 -1.560577e+03 -2.5 2.5
#> 56 0.0146404640 -5.929544e+02 -2.5 2.5
#> 57 0.0168475924 -6.311830e+02 -2.5 2.5
#> 58 0.0207885305 -3.293111e+02 -2.5 2.5
#> 59 0.0369584560 5.367628e+01 -2.5 2.5
#> 60 0.0328598686 -2.798862e+03 -2.5 2.5
#> 61 0.0136606791 -3.541047e+00 -2.5 2.5
#> 62 0.0089644687 -5.519056e+02 -2.5 2.5
#> 63 0.0446239135 1.259608e+03 -2.5 2.5
#> 64 0.0086025384 3.167386e+03 -2.5 2.5
#> 65 0.0094356784 -1.163297e+04 -2.5 2.5
#> 66 0.0152091897 3.330926e+02 -2.5 2.5
#> 67 0.0468824858 9.000553e+01 -2.5 2.5
#> 68 0.0197406134 1.634749e+03 -2.5 2.5
#> 69 NaN NA -2.5 2.5
#> 70 0.0206317923 4.719081e+02 -2.5 2.5
#> 71 0.0338079759 2.483902e+03 -2.5 2.5
#> 72 0.0138841127 1.067184e+03 -2.5 2.5
#> 73 0.0177600090 -1.103202e+03 -2.5 2.5
#> 74 0.0251252886 4.411402e+01 -2.5 2.5
#> 75 0.0118652434 -1.081458e+03 -2.5 2.5
#> 76 0.0145672064 2.561792e+03 -2.5 2.5
#> 77 0.0768215880 -3.929280e+03 -2.5 2.5
#> 78 0.0336566208 -2.490769e+03 -2.5 2.5
#> 79 0.0169279013 1.625083e+03 -2.5 2.5
#> 80 0.0230948769 -1.490240e+03 -2.5 2.5
#> 81 0.0705804137 -7.593794e+02 -2.5 2.5
#> 82 0.0296752116 2.488547e+02 -2.5 2.5
#> 83 0.0157930320 -3.068981e+03 -2.5 2.5
#> 84 0.0172194380 -1.069035e+03 -2.5 2.5
#> 85 0.0210434090 3.642313e+02 -2.5 2.5
#> 86 0.0151075989 2.018387e+03 -2.5 2.5
#> 87 0.0122078946 5.684143e+01 -2.5 2.5
#> 88 0.0181316516 -1.126714e+03 -2.5 2.5
#> 89 0.0253285544 -7.707320e+02 -2.5 2.5
#> 90 0.0212574371 1.316490e+04 -2.5 2.5
#> 91 0.0084575764 -1.734677e+04 -2.5 2.5
#> 92 0.0093304792 -3.006315e+03 -2.5 2.5
#> 93 0.0226108574 -8.005165e+02 -2.5 2.5
#> 94 0.0245020875 8.221896e+02 -2.5 2.5
#> 95 0.0192691030 5.611274e+02 -2.5 2.5
#> 96 0.0257784785 1.420777e+03 -2.5 2.5
#> 97 0.0136381553 4.652264e+02 -2.5 2.5
#> 98 0.0421951132 -2.842468e+03 -2.5 2.5
#> 99 0.0402783749 -2.135529e+03 -2.5 2.5
#> 100 0.0197758883 -1.122811e+03 -2.5 2.5
#> 101 0.0316750902 -4.212439e+02 -2.5 2.5
#> 102 0.0710906336 -3.061082e+02 -2.5 2.5
#> 103 0.0464885266 2.061834e+03 -2.5 2.5
#> 104 0.0076491707 -1.022825e+04 -2.5 2.5
#> 105 0.0080561914 4.595257e+03 -2.5 2.5
#> 106 0.0067289909 -8.961960e+03 -2.5 2.5
#> 107 0.0240371602 -3.064346e+03 -2.5 2.5
#> 108 0.0375784916 4.401605e+02 -2.5 2.5
#> 109 0.0223655914 -4.940044e+02 -2.5 2.5
#> 110 0.0405894066 4.636400e+02 -2.5 2.5
#> 111 0.0085092367 -1.449445e+04 -2.5 2.5
#> 112 0.0274283584 -1.427017e+03 -2.5 2.5
#> 113 0.0132363121 3.006290e+03 -2.5 2.5
#> 114 0.0143459131 -8.798302e+03 -2.5 2.5
#> 115 0.0137344428 -1.405660e+04 -2.5 2.5
#> 116 0.0168640610 -1.351228e+03 -2.5 2.5
#> 117 0.0479142831 -2.892525e+02 -2.5 2.5
#> 118 0.0178106875 1.134505e+03 -2.5 2.5
#> 119 0.0312782970 -8.632000e+02 -2.5 2.5
#> 120 0.0305977303 -5.580609e+02 -2.5 2.5
#> 121 0.0297674680 -8.415135e+02 -2.5 2.5
#> 122 0.0067693799 -6.647795e+03 -2.5 2.5
#> 123 0.0692118124 -3.399273e+02 -2.5 2.5
#> 124 0.0344457903 -7.522353e+02 -2.5 2.5
#> 125 0.0112572524 -1.022785e+04 -2.5 2.5
#> 126 0.0168919839 3.898047e+04 -2.5 2.5
#> 127 0.0297496649 3.384633e+03 -2.5 2.5
#> 128 0.0325104771 -5.989894e+02 -2.5 2.5
#> 129 0.0470728179 -1.037549e+03 -2.5 2.5
#> 130 0.0248136113 -5.321292e+02 -2.5 2.5
#> 131 0.0232895996 1.832768e+02 -2.5 2.5
#> 132 0.0152853905 -1.341626e+03 -2.5 2.5
#> 133 0.0142724468 -2.908355e+03 -2.5 2.5
#> 134 0.0603984796 -8.796946e+02 -2.5 2.5
#> 135 0.0349798601 -1.153024e+03 -2.5 2.5
#> 136 0.0367987589 -5.347504e+02 -2.5 2.5
#> 137 0.0168421645 -1.282381e+01 -2.5 2.5
#> 138 0.0137845599 1.992413e+03 -2.5 2.5
#> 139 0.0329204024 -8.663907e+01 -2.5 2.5
#> 140 0.0210752688 8.636472e+02 -2.5 2.5
#> 141 0.0201167956 6.736049e+02 -2.5 2.5
#> 142 0.0333816996 -2.792979e+03 -2.5 2.5
#> 143 0.0161883841 -1.540199e+03 -2.5 2.5
#> 144 0.0070602431 -5.702579e+03 -2.5 2.5
#> 145 0.0138740822 -4.297146e+03 -2.5 2.5
#> 146 0.0139253336 -8.616389e+02 -2.5 2.5
#> 147 0.0283474653 1.893954e+03 -2.5 2.5
#> 148 0.0309945680 -1.471592e+03 -2.5 2.5
#> 149 0.0131425350 8.576815e+03 -2.5 2.5
#> 150 0.0247434305 -1.305836e+03 -2.5 2.5
#> 151 0.0289824878 -1.422567e+03 -2.5 2.5
#> 152 0.0294225408 3.785219e+01 -2.5 2.5
#> 153 NaN NA -2.5 2.5
#> 154 0.0498726035 3.829621e+01 -2.5 2.5
#> 155 0.0191796097 1.112806e+02 -2.5 2.5
#> 156 0.0197849462 2.404418e+03 -2.5 2.5
#> 157 0.0002958727 3.502324e+03 -2.5 2.5
#> 158 0.0276921208 2.326416e+04 -2.5 2.5
#> 159 0.0518876908 6.993804e+03 -2.5 2.5
#> 160 0.0227035069 6.882355e+03 -2.5 2.5
#> 161 0.0212788356 2.361981e+03 -2.5 2.5
#> 162 0.0478079130 -8.385423e+02 -2.5 2.5
#> 163 0.0330818310 1.317664e+03 -2.5 2.5
#> 164 0.0287536836 -2.666321e+03 -2.5 2.5
#> 165 0.1294224031 1.264726e+03 -2.5 2.5
#> 166 0.0150059737 1.705592e+02 -2.5 2.5
#> 167 0.0989035831 -1.548219e+02 -2.5 2.5
#> 168 0.0278337744 -1.915824e+02 -2.5 2.5
#> 169 0.0198775578 4.476183e+03 -2.5 2.5
#> 170 0.0388291926 -5.186302e+02 -2.5 2.5
#> 171 0.0352213036 -4.233724e+03 -2.5 2.5
#> 172 0.0005735860 -4.277393e+02 -2.5 2.5
#> 173 0.0770071225 1.501444e+03 -2.5 2.5
#> 174 0.0234256049 2.536164e+02 -2.5 2.5
#> 175 0.0415298842 5.656228e+04 -2.5 2.5
#> 176 0.0115690929 4.898772e+03 -2.5 2.5
#> 177 0.0461272851 -1.019675e+03 -2.5 2.5
#> 178 0.0182611634 4.043655e+03 -2.5 2.5
#> 179 0.0159074272 -4.111156e+02 -2.5 2.5
#> 180 0.0474742213 -6.234281e+03 -2.5 2.5
#> 181 0.0484420406 1.219713e+03 -2.5 2.5
#> 182 0.0620553928 -2.861462e+03 -2.5 2.5
#> 183 0.0396049198 -5.025428e+02 -2.5 2.5
#> 184 0.0081704703 6.120839e+03 -2.5 2.5
#> 185 0.0358759828 5.952699e+03 -2.5 2.5
#> 186 0.0003876089 5.979570e+02 -2.5 2.5
#> 187 0.0416464794 -4.087436e+03 -2.5 2.5
#> 188 0.0245145457 2.187486e+02 -2.5 2.5
#> 189 0.0012220013 1.730948e+03 -2.5 2.5
#> 190 0.0421861565 3.868387e+03 -2.5 2.5
#> 191 0.0181372825 -1.127070e+03 -2.5 2.5
#> 192 0.0273438820 -1.823457e+02 -2.5 2.5
#> 193 0.0296145586 -1.351194e-02 -2.5 2.5
#> 194 0.0197339904 -2.664753e+02 -2.5 2.5
#> 195 0.0643358538 -4.181400e+03 -2.5 2.5
#> 196 0.0132084469 -1.400279e+04 -2.5 2.5
#> 197 0.0113032666 5.007158e+02 -2.5 2.5
#> 198 0.0205583121 -1.860419e+03 -2.5 2.5
#> 199 0.0868491309 3.141227e+04 -2.5 2.5
#> 200 0.0571683166 -5.636755e+02 -2.5 2.5
#> 201 0.0130840509 -1.357839e+03 -2.5 2.5
#> 202 0.0275530041 -5.947921e+03 -2.5 2.5
#> 203 0.0627336851 -3.232892e+03 -2.5 2.5
#> 204 0.0281241043 -2.340357e+03 -2.5 2.5
#> 205 0.0157497607 -8.046286e+02 -2.5 2.5
#> 206 0.0310456714 -6.175157e+03 -2.5 2.5
#> 207 0.0175866189 -6.298802e+02 -2.5 2.5
#> 208 0.0408098368 6.519673e+02 -2.5 2.5
#> 209 0.0191508531 -7.796321e+01 -2.5 2.5
#> 210 0.0002896109 7.822490e+02 -2.5 2.5
#> 211 0.0177777778 7.606335e+00 -2.5 2.5
#> 212 0.0209887528 -2.745419e+02 -2.5 2.5
#> 213 0.0337452950 7.329006e+02 -2.5 2.5
#> 214 0.0198260918 8.268953e+02 -2.5 2.5
#> 215 0.0218255532 1.056414e+02 -2.5 2.5
#> 216 0.0218812697 -1.224440e+03 -2.5 2.5
#> 217 0.0659647622 -8.325013e+03 -2.5 2.5
#> 218 0.0458404987 -1.787280e+03 -2.5 2.5
#> 219 0.0233058564 -3.594903e+03 -2.5 2.5
#> 220 0.0077866185 -8.675087e+03 -2.5 2.5
#> 221 0.0088855743 -8.216476e+03 -2.5 2.5
#> 222 0.0369464746 1.127615e+03 -2.5 2.5
#> 223 0.0001192884 -2.426240e+02 -2.5 2.5
#> 224 0.0410082769 -1.595660e+03 -2.5 2.5
#> 225 0.0261025591 -4.037853e+03 -2.5 2.5
#> 226 0.0434580109 -8.307703e+02 -2.5 2.5
#> 227 0.0261655174 6.703799e+02 -2.5 2.5
#> 228 0.0919075213 -4.694933e+03 -2.5 2.5
#> 229 0.0160932485 3.071517e+03 -2.5 2.5
#> 230 0.0131407843 1.133970e+03 -2.5 2.5
#> 231 0.0270967742 6.049655e+02 -2.5 2.5
#> 232 0.0278922116 8.235227e+03 -2.5 2.5
#> 233 0.0540688522 -8.000601e+02 -2.5 2.5
#> 234 0.0179088814 4.147572e+02 -2.5 2.5
#> 235 0.0788402848 -9.434732e+01 -2.5 2.5
#> 236 0.0372689166 9.431373e+03 -2.5 2.5
#> 237 0.0240846231 -1.995915e+03 -2.5 2.5
#> 238 0.0295211370 6.541025e+02 -2.5 2.5
#> 239 0.0129399178 1.628557e+03 -2.5 2.5
#> 240 0.0261927754 -3.644506e+03 -2.5 2.5
#> 241 0.0005522957 -1.123817e+03 -2.5 2.5
#> 242 0.0345997611 -1.261060e+03 -2.5 2.5
#> 243 0.0315584293 4.154019e+03 -2.5 2.5
#> 244 0.0299919911 7.718457e+03 -2.5 2.5
#> 245 0.0420895813 -9.264968e+02 -2.5 2.5
#> 246 0.0159355820 1.084344e+02 -2.5 2.5
#> 247 0.0165662481 -7.379989e+02 -2.5 2.5
#> 248 NaN NA -2.5 2.5
#> 249 0.0431033043 -7.541934e+02 -2.5 2.5
#> 250 0.0159918914 -8.960589e+02 -2.5 2.5
#> 251 0.0612664277 -1.488943e+03 -2.5 2.5
#> 252 0.0141437819 -1.225952e+03 -2.5 2.5
#> 253 0.0386227253 -8.471167e+02 -2.5 2.5
#> 254 0.0140712616 -5.040847e+01 -2.5 2.5
#> 255 0.0678195999 -4.373227e+02 -2.5 2.5
#> 256 0.0135308690 5.633102e+03 -2.5 2.5
#> 257 0.0369419792 1.457825e+02 -2.5 2.5
#> 258 0.0083695973 7.244501e+03 -2.5 2.5
#> 259 0.0146361501 -7.017036e+03 -2.5 2.5
#> 260 0.0076789145 -8.193418e+03 -2.5 2.5
#> 261 0.0183343657 -5.567373e+01 -2.5 2.5
#> 262 0.0356292553 -3.590719e+02 -2.5 2.5
#> 263 0.0299785152 -1.127174e+03 -2.5 2.5
#> 264 0.0197208206 1.519568e+03 -2.5 2.5
#> 265 0.0267427358 2.367228e+02 -2.5 2.5
#> 266 0.0211408132 -3.787053e+03 -2.5 2.5
#> 267 0.0550264387 8.312328e+02 -2.5 2.5
#> 268 0.0321623992 2.500237e+03 -2.5 2.5
#> 269 0.0263162087 -3.337450e+02 -2.5 2.5
#> 270 0.0258910975 -1.148454e+03 -2.5 2.5
#> 271 NaN NA -2.5 2.5
#> 272 0.0195989806 1.287699e+03 -2.5 2.5
#> 273 0.0643247985 2.222617e+03 -2.5 2.5
#> 274 0.0228599445 -8.549810e+02 -2.5 2.5
#> 275 0.0189347950 -2.083367e+03 -2.5 2.5
#> 276 0.0474143707 -1.713679e+03 -2.5 2.5
#> 277 0.0154655213 -9.767517e+02 -2.5 2.5
#> 278 0.0175264991 -5.678446e+02 -2.5 2.5
#> 279 0.0167239146 -4.743255e+02 -2.5 2.5
#> 280 0.1180061038 -8.042399e+02 -2.5 2.5
#> 281 0.0289736044 -4.176442e+02 -2.5 2.5
#> 282 0.0011014605 -4.705432e+02 -2.5 2.5
#> 283 0.0500788522 -1.699951e+03 -2.5 2.5
#> 284 0.0482714451 1.129680e+03 -2.5 2.5
#> 285 0.0136291222 -1.144275e+03 -2.5 2.5
#> 286 0.0146010474 1.726526e+02 -2.5 2.5
#> 287 0.0174728307 -8.761823e+01 -2.5 2.5
#> 288 0.0421642758 1.379255e+03 -2.5 2.5
#> 289 0.0139636510 2.660058e+03 -2.5 2.5
#> 290 0.0114646095 -7.076142e+02 -2.5 2.5
#> 291 0.0352930441 4.809785e+02 -2.5 2.5
#> 292 0.0341059339 -9.840768e+01 -2.5 2.5
#> 293 0.0316709659 -8.224367e+02 -2.5 2.5
#> 294 0.0586588794 -4.456805e+04 -2.5 2.5
#> 295 0.0239878372 1.878466e+03 -2.5 2.5
#> 296 NaN NA -2.5 2.5
#> 297 0.0413979650 -3.478044e+03 -2.5 2.5
#> 298 0.0429833047 4.824631e+02 -2.5 2.5
#> 299 0.0174050474 2.434228e+03 -2.5 2.5
#> 300 0.0979428055 5.335203e+02 -2.5 2.5
#> 301 0.0155427203 -3.070307e+03 -2.5 2.5
#> 302 0.0269102990 4.111594e+02 -2.5 2.5
#> 303 0.0184244608 -1.143213e+03 -2.5 2.5
#> 304 0.0219241211 -3.137506e+02 -2.5 2.5
#> 305 0.0222663290 2.580848e+02 -2.5 2.5
#> 306 0.0161088458 2.039034e+03 -2.5 2.5
#> 307 0.0144264880 5.902982e+02 -2.5 2.5
#> 308 0.0222647672 -1.389397e+03 -2.5 2.5
#> 309 0.0300790088 4.284439e+03 -2.5 2.5
#> 310 0.0131823041 -2.931273e+03 -2.5 2.5
#> 311 0.0114364548 1.242425e+03 -2.5 2.5
#> 312 0.0324582290 3.544248e+03 -2.5 2.5
#> 313 0.0411029566 7.437333e+03 -2.5 2.5
#> 314 0.0198032696 -6.550644e+02 -2.5 2.5
#> 315 0.0141929085 -1.116235e+03 -2.5 2.5
#> 316 0.0459033484 7.839328e+03 -2.5 2.5
#> 317 0.0575303176 8.445001e+02 -2.5 2.5
#> 318 NaN 2.936006e+03 -2.5 2.5
#> 319 0.0068194747 -1.182632e+04 -2.5 2.5
#> 320 0.0304350979 3.102974e+03 -2.5 2.5
#> 321 0.0225978074 2.200120e+03 -2.5 2.5
#> 322 0.0072975675 9.075267e+03 -2.5 2.5
#> 323 0.0366317196 -8.017873e+02 -2.5 2.5
#> 324 0.1995591726 1.142493e+02 -2.5 2.5
#> 325 0.0655237051 1.708507e+04 -2.5 2.5
#> 326 0.0497358670 -4.410255e+03 -2.5 2.5
#> 327 0.0142294048 -4.008974e+02 -2.5 2.5
#> 328 0.0370040837 -5.378488e+02 -2.5 2.5
#> 329 0.0191584265 -1.579702e+03 -2.5 2.5
#> 330 0.0313690598 9.703668e+02 -2.5 2.5
#> 331 0.0074711270 3.437776e+01 -2.5 2.5
#> 332 0.0138112306 -4.927677e+02 -2.5 2.5
#> 333 0.0392831541 1.952483e+03 -2.5 2.5
#> 334 0.0285173271 -4.108741e+02 -2.5 2.5
#> 335 0.0215383749 -1.004784e+03 -2.5 2.5
#> 336 0.0357748389 -1.348674e+02 -2.5 2.5
#> 337 0.0251636895 5.414636e+01 -2.5 2.5
#> 338 0.0392931356 2.130897e+03 -2.5 2.5
#> 339 0.0119915689 -2.048916e+03 -2.5 2.5
#> 340 0.0128213903 -1.817918e+02 -2.5 2.5
#> 341 0.0158351405 -3.396537e+03 -2.5 2.5
#> 342 0.0158074304 1.225879e+02 -2.5 2.5
#> 343 0.0439495914 4.457934e+03 -2.5 2.5
#> 344 0.0334223074 -4.839880e+02 -2.5 2.5
#> 345 0.0181911006 -2.497485e+02 -2.5 2.5
#> 346 0.0186259992 1.121735e+03 -2.5 2.5
#> 347 NaN NA -2.5 2.5
#> 348 NaN NA -2.5 2.5
#> 349 NaN NA -2.5 2.5
#> 350 0.0437954915 -1.084538e+03 -2.5 2.5
#> 351 0.0124781801 -1.694582e+02 -2.5 2.5
#> 352 0.0790697948 -2.409620e+03 -2.5 2.5
#> 353 0.0333538658 -4.602036e+02 -2.5 2.5
#> 354 0.0233373158 3.131616e+02 -2.5 2.5
#> 355 NaN NA -2.5 2.5
#> 356 0.0292791716 -6.966132e+02 -2.5 2.5
#> 357 0.0401798510 -1.541482e+03 -2.5 2.5
#> 358 0.0081526240 3.656936e+03 -2.5 2.5
#> 359 NaN NA -2.5 2.5
#> 360 NaN NA -2.5 2.5
#> 361 0.0289279766 -4.025498e+02 -2.5 2.5
#> 362 0.0381068476 -3.457707e+03 -2.5 2.5
#> 363 0.0325448029 -4.146150e+02 -2.5 2.5
#> 364 0.0164715253 -5.892733e+02 -2.5 2.5
#> 365 NaN NA -2.5 2.5
#> 366 0.0565566627 2.855206e+02 -2.5 2.5
#> 367 NaN NA -2.5 2.5
#> 368 0.0227769418 4.962171e+02 -2.5 2.5
#> 369 NaN NA -2.5 2.5
#> 370 NaN NA -2.5 2.5
#> 371 0.0489129195 8.877903e+02 -2.5 2.5
#> 372 NaN NA -2.5 2.5
#> 373 NaN NA -2.5 2.5
#> 374 NaN NA -2.5 2.5
#> 375 0.0087773795 -2.893809e+02 -2.5 2.5
#> 376 0.0432349949 -2.716295e+02 -2.5 2.5
#> 377 0.0304793192 -2.884096e+02 -2.5 2.5
#> 378 0.0261961742 -3.891241e+03 -2.5 2.5
#> 379 0.0218730335 -2.051539e+03 -2.5 2.5
#> 380 0.0189067226 7.728533e+02 -2.5 2.5
#> 381 NaN NA -2.5 2.5
#> 382 0.0255025621 5.633536e+02 -2.5 2.5
#> 383 0.0238942421 4.421462e+03 -2.5 2.5
#> 384 0.0116500221 6.279159e+02 -2.5 2.5
#> 385 0.0242283211 -3.475442e+02 -2.5 2.5
#> 386 0.0230060605 -1.527246e+04 -2.5 2.5
#> 387 0.0077318272 -3.538237e+01 -2.5 2.5
#> 388 0.0482516926 2.528206e+03 -2.5 2.5
#> 389 0.0171237119 1.063424e+03 -2.5 2.5
#> 390 0.0223496615 1.069961e+02 -2.5 2.5
#> 391 0.0259393608 -3.727419e+02 -2.5 2.5
#> 392 0.0167423337 -5.991265e+02 -2.5 2.5
#> 393 NaN NA -2.5 2.5
#> 394 0.0006981970 2.203625e+03 -2.5 2.5
#> 395 0.0157696384 2.082461e+03 -2.5 2.5
#> 396 NaN NA -2.5 2.5
#> 397 0.0264184519 -2.298514e+02 -2.5 2.5
#> 398 0.0352017886 -5.106969e+02 -2.5 2.5
#> 399 0.0515994122 -3.270391e+02 -2.5 2.5
#> 400 0.0208746835 -6.861527e+01 -2.5 2.5
#> 401 0.0684168374 -8.420773e+03 -2.5 2.5
#> 402 0.0133367020 -2.244446e+03 -2.5 2.5
#> 403 0.0363520510 -2.927244e+02 -2.5 2.5
#> 404 0.0455754679 -1.060973e+03 -2.5 2.5
#> 405 0.0297092792 1.612847e+01 -2.5 2.5
#> 406 0.0342493031 -6.317324e+02 -2.5 2.5
#> 407 0.0261536257 -1.526087e+03 -2.5 2.5
#> 408 0.0438431499 -2.694971e+03 -2.5 2.5
#> 409 0.0196097172 -7.037886e+02 -2.5 2.5
#> 410 0.0191405130 6.952077e+03 -2.5 2.5
#> 411 0.0362754105 -3.302478e+03 -2.5 2.5
#> 412 0.0615680871 9.827466e+03 -2.5 2.5
#> 413 0.0264760676 -4.450347e+02 -2.5 2.5
#> 414 0.1183485266 -2.587932e+03 -2.5 2.5
#> 415 0.0151493429 -5.412443e+02 -2.5 2.5
#> 416 0.0167901235 -5.764561e+02 -2.5 2.5
#> 417 0.0164874552 -5.096793e+01 -2.5 2.5
#> 418 0.0193548387 -2.857237e+01 -2.5 2.5
#> 419 0.0293422184 3.801011e+02 -2.5 2.5
#> 420 0.0356298366 -2.988026e+03 -2.5 2.5
#> 421 0.0238965320 2.156911e+03 -2.5 2.5
#> 422 0.0209956193 9.481552e+02 -2.5 2.5
#> 423 0.0181441657 9.477760e+02 -2.5 2.5
#> 424 0.0159299084 4.953816e+02 -2.5 2.5
#> 425 NaN NA -2.5 2.5
#> 426 NaN NA -2.5 2.5
#> 427 NaN NA -2.5 2.5
#> 428 0.0602254258 1.130379e+04 -2.5 2.5
#>
#> $aggregates
#> strata N coef coefB nModel sigmaHat
#> 1 13 63 0.6367325 0 62 56.73678
#> 2 3 35 0.7243748 0 32 46.93056
#> 3 5 40 0.3193256 0 33 15.33552
#> 4 1 21 0.2935828 0 21 19.83498
#> 5 4 15 0.3397197 0 13 14.52166
#> 6 10 21 0.2986332 0 21 23.25865
#> 7 11 53 0.5133332 0 53 35.48844
#> 8 8 23 0.5033864 0 23 40.69596
#> 9 2 60 0.3435666 0 54 19.58185
#> 10 7 31 0.3194187 0 31 25.88260
#> 11 6 47 0.5605098 0 40 20.04180
#> 12 12 19 0.8272207 0 19 53.12696
#>
#> $total
#> Ntotal
#> 1 428
#>