Running ‘Distributions.R’ [2s/3s]
  Comparing ‘Distributions.Rout’ to ‘Distributions.Rout.save’ ... OK
  Running ‘LinearStatistic-regtest.R’ [2s/3s]
  Comparing ‘LinearStatistic-regtest.Rout’ to ‘LinearStatistic-regtest.Rout.save’ ... OK
  Running ‘Predict-regtest.R’ [4s/5s]
  Comparing ‘Predict-regtest.Rout’ to ‘Predict-regtest.Rout.save’ ... OK
  Running ‘RandomForest-regtest.R’ [5s/7s]
  Comparing ‘RandomForest-regtest.Rout’ to ‘RandomForest-regtest.Rout.save’ ... OK
  Running ‘TestStatistic-regtest.R’ [2s/3s]
  Comparing ‘TestStatistic-regtest.Rout’ to ‘TestStatistic-regtest.Rout.save’ ... OK
  Running ‘TreeGrow-regtest.R’ [5s/6s]
  Comparing ‘TreeGrow-regtest.Rout’ to ‘TreeGrow-regtest.Rout.save’ ... OK
  Running ‘Utils-regtest.R’ [2s/3s]
  Comparing ‘Utils-regtest.Rout’ to ‘Utils-regtest.Rout.save’ ... OK
  Running ‘bugfixes.R’ [11s/14s]
  Comparing ‘bugfixes.Rout’ to ‘bugfixes.Rout.save’ ... OK
  Running ‘mob.R’ [3s/3s]
Running the tests in ‘tests/mob.R’ failed.
Complete output:
  > library("party")
  Loading required package: grid
  Loading required package: mvtnorm
  Loading required package: modeltools
  Loading required package: stats4
  Loading required package: strucchange
  Loading required package: zoo
  
  Attaching package: 'zoo'
  
  The following objects are masked from 'package:base':
  
      as.Date, as.Date.numeric
  
  Loading required package: sandwich
  > 
  > data("BostonHousing", package = "mlbench")
  > BostonHousing$lstat <- log(BostonHousing$lstat)
  > BostonHousing$rm <- BostonHousing$rm^2
  > BostonHousing$chas <- factor(BostonHousing$chas, levels = 0:1, labels = c("no", "yes"))
  > BostonHousing$rad <- factor(BostonHousing$rad, ordered = TRUE)
  > fmBH <- mob(medv ~ lstat + rm | zn + indus + chas + nox + age + dis + rad + tax + crim + b + ptratio,
  +   control = mob_control(minsplit = 40, verbose = TRUE),
  +   data = BostonHousing, model = linearModel)
  
  -------------------------------------------
  Fluctuation tests of splitting variables:
                      zn        indus         chas          nox          age
  statistic 3.363356e+01 6.532322e+01 2.275635e+01 8.136281e+01 3.675850e+01
  p.value   1.023987e-04 1.363602e-11 4.993053e-04 3.489797e-15 2.263798e-05
                     dis          rad          tax         crim            b
  statistic 6.848533e+01 1.153641e+02 9.068440e+01 8.655065e+01 3.627629e+01
  p.value   2.693904e-12 7.087680e-13 2.735524e-17 2.356348e-16 2.860686e-05
                 ptratio
  statistic 7.221524e+01
  p.value   3.953623e-13
  
  Best splitting variable: tax
  Perform split? yes
  -------------------------------------------
  
  Node properties:
  tax <= 432; criterion = 1, statistic = 115.364
  
  -------------------------------------------
  Fluctuation tests of splitting variables:
                      zn      indus      chas          nox        age
  statistic 27.785009791 21.3329346 8.0272421 23.774323202 11.9204284
  p.value    0.001494064  0.0285193 0.4005192  0.009518732  0.7666366
                     dis          rad          tax         crim         b
  statistic 24.268011081 50.481593270 3.523250e+01 3.276813e+01 9.0363245
  p.value    0.007601532  0.003437763 4.275527e-05 1.404487e-04 0.9871502
                 ptratio
  statistic 4.510680e+01
  p.value   3.309747e-07
  
  Best splitting variable: ptratio
  Perform split? yes
  -------------------------------------------
  
  Node properties:
  ptratio <= 15.2; criterion = 1, statistic = 50.482
  
  -------------------------------------------
  Fluctuation tests of splitting variables:
                      zn       indus        chas         nox         age
  statistic 3.233350e+01 22.26864036 12.93407112 22.10510234 20.41295354
  p.value   1.229678e-04  0.01504788  0.05259509  0.01622098  0.03499731
                   dis          rad          tax        crim         b
  statistic 17.7204735 5.526565e+01 2.879128e+01 20.28503194 6.5549665
  p.value    0.1091769 7.112214e-04 6.916307e-04  0.03706934 0.9999522
                 ptratio
  statistic 4.789850e+01
  p.value   4.738855e-08
  
  Best splitting variable: ptratio
  Perform split? yes
  -------------------------------------------
  
  Node properties:
  ptratio <= 19.6; criterion = 1, statistic = 55.266
  
  -------------------------------------------
  Fluctuation tests of splitting variables:
                   zn      indus      chas        nox       age        dis
  statistic 14.971474 14.6477733 7.1172962 14.3455158 8.2176363 16.1112185
  p.value    0.280361  0.3134649 0.5405005  0.3467974 0.9906672  0.1847818
                    rad          tax     crim         b    ptratio
  statistic 43.17824350 3.447271e+01 9.340075 8.7773142 10.8469969
  p.value    0.03281124 4.281939e-05 0.952996 0.9772696  0.8202694
  
  Best splitting variable: tax
  Perform split? yes
  -------------------------------------------
  
  Node properties:
  tax <= 265; criterion = 1, statistic = 43.178
  
  -------------------------------------------
  Fluctuation tests of splitting variables:
                   zn     indus     chas       nox        age       dis
  statistic 11.998039 7.3971233 7.227770 9.2936189 14.3023962 8.9239826
  p.value    0.574642 0.9931875 0.522447 0.9119621  0.2886603 0.9389895
                   rad        tax       crim         b    ptratio
  statistic 33.1746444 16.6666129 11.7143758 9.9050903 11.5927528
  p.value    0.3926249  0.1206412  0.6153455 0.8539893  0.6328381
  
  Best splitting variable: tax
  Perform split? no
  -------------------------------------------
  
  -------------------------------------------
  Fluctuation tests of splitting variables:
                    zn     indus         chas         nox       age        dis
  statistic 10.9187926 9.0917078 2.754081e+01 17.39203006 4.6282349 11.9581600
  p.value    0.7091039 0.9172303 4.987667e-05  0.08922543 0.9999992  0.5607267
                  rad        tax     crim        b   ptratio
  statistic 0.2557803 10.9076165 3.711175 3.158329 9.8865054
  p.value   1.0000000  0.7106612 1.000000 1.000000 0.8410064
  
  Best splitting variable: chas
  Perform split? yes
  -------------------------------------------
  
  Splitting factor variable, objective function: 
   no 
  Inf 
  
  No admissable split found in 'chas'
  > fmBH
  1) tax <= 432; criterion = 1, statistic = 115.364
    2) ptratio <= 15.2; criterion = 1, statistic = 50.482
      3)*  weights = 72 
  Terminal node model
  Linear model with coefficients:
  (Intercept)        lstat           rm  
       9.2349      -4.9391       0.6859  
  
    2) ptratio > 15.2
      4) ptratio <= 19.6; criterion = 1, statistic = 55.266
        5) tax <= 265; criterion = 1, statistic = 43.178
          6)*  weights = 63 
  Terminal node model
  Linear model with coefficients:
  (Intercept)        lstat           rm  
       3.9637      -2.7663       0.6881  
  
        5) tax > 265
          7)*  weights = 162 
  Terminal node model
  Linear model with coefficients:
  (Intercept)        lstat           rm  
      -1.7984      -0.2677       0.6539  
  
      4) ptratio > 19.6
        8)*  weights = 56 
  Terminal node model
  Linear model with coefficients:
  (Intercept)        lstat           rm  
      17.5865      -4.6190       0.3387  
  
  1) tax > 432
    9)*  weights = 153 
  Terminal node model
  Linear model with coefficients:
  (Intercept)        lstat           rm  
      68.2971     -16.3540      -0.1478  
  
  > summary(fmBH)
  $`3`
  
  Call:
  NULL
  
  Weighted Residuals:
     Min     1Q Median     3Q    Max 
  -7.910  0.000  0.000  0.000  6.632 
  
  Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
  (Intercept)  9.23488    3.95128   2.337   0.0223 *  
  lstat       -4.93910    0.88285  -5.595 4.14e-07 ***
  rm           0.68591    0.05136  13.354  < 2e-16 ***
  ---
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  
  Residual standard error: 3.413 on 69 degrees of freedom
  Multiple R-squared:  0.922,	Adjusted R-squared:  0.9197 
  F-statistic: 407.8 on 2 and 69 DF,  p-value: < 2.2e-16
  
  
  $`6`
  
  Call:
  NULL
  
  Weighted Residuals:
     Min     1Q Median     3Q    Max 
  -4.614  0.000  0.000  0.000 12.473 
  
  Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
  (Intercept)  3.96372    5.00781   0.792  0.43177    
  lstat       -2.76629    1.00406  -2.755  0.00776 ** 
  rm           0.68813    0.07716   8.918 1.36e-12 ***
  ---
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  
  Residual standard error: 3.2 on 60 degrees of freedom
  Multiple R-squared:  0.8176,	Adjusted R-squared:  0.8115 
  F-statistic: 134.5 on 2 and 60 DF,  p-value: < 2.2e-16
  
  
  $`7`
  
  Call:
  NULL
  
  Weighted Residuals:
     Min     1Q Median     3Q    Max 
  -9.092  0.000  0.000  0.000 10.236 
  
  Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
  (Intercept) -1.79839    2.84702  -0.632    0.529    
  lstat       -0.26771    0.69581  -0.385    0.701    
  rm           0.65389    0.03757  17.404   <2e-16 ***
  ---
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  
  Residual standard error: 2.652 on 159 degrees of freedom
  Multiple R-squared:  0.8173,	Adjusted R-squared:  0.815 
  F-statistic: 355.6 on 2 and 159 DF,  p-value: < 2.2e-16
  
  
  $`8`
  
  Call:
  NULL
  
  Weighted Residuals:
     Min     1Q Median     3Q    Max 
  -8.466  0.000  0.000  0.000  4.947 
  
  Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
  (Intercept) 17.58649    4.21666   4.171 0.000113 ***
  lstat       -4.61897    0.84025  -5.497 1.13e-06 ***
  rm           0.33867    0.07574   4.472 4.13e-05 ***
  ---
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  
  Residual standard error: 2.197 on 53 degrees of freedom
  Multiple R-squared:  0.6446,	Adjusted R-squared:  0.6312 
  F-statistic: 48.07 on 2 and 53 DF,  p-value: 1.238e-12
  
  
  $`9`
  
  Call:
  NULL
  
  Weighted Residuals:
     Min     1Q Median     3Q    Max 
  -10.56   0.00   0.00   0.00  24.28 
  
  Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
  (Intercept)  68.29709    3.83284  17.819  < 2e-16 ***
  lstat       -16.35401    0.96577 -16.934  < 2e-16 ***
  rm           -0.14779    0.05047  -2.928  0.00394 ** 
  ---
  Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  
  Residual standard error: 4.689 on 150 degrees of freedom
  Multiple R-squared:  0.6649,	Adjusted R-squared:  0.6604 
  F-statistic: 148.8 on 2 and 150 DF,  p-value: < 2.2e-16
  
  
  > 
  > ### check for one-node tree
  > fmBH <- try(mob(medv ~ lstat + rm | zn, control = mob_control(minsplit = 4000, verbose = TRUE),
  +   data = BostonHousing, model = linearModel))
  > stopifnot(class(fmBH) != "try-error")
  > 
  > 
  > data("PimaIndiansDiabetes", package = "mlbench")
  Warning message:
  In data("PimaIndiansDiabetes", package = "mlbench") :
    data set 'PimaIndiansDiabetes' not found
  > fmPID <- mob(diabetes ~ glucose | pregnant + pressure + triceps + insulin + mass + pedigree + age,
  +   control = mob_control(verbose = TRUE),
  +   data = PimaIndiansDiabetes, model = glinearModel, family = binomial())
  Error: object 'PimaIndiansDiabetes' not found
  Execution halted