266 lines (205 with data), 8.4 kB
> require("party")
Loading required package: party
Loading required package: grid
Loading required package: zoo
Attaching package: ‘zoo’
The following objects are masked from ‘package:base’:
as.Date, as.Date.numeric
Loading required package: sandwich
Loading required package: strucchange
Loading required package: modeltools
Loading required package: stats4
> options(useFancyQuotes = FALSE)
> library("party")
> 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)
> ctrl <- mob_control(alpha = 0.05, bonferroni = TRUE,
+ minsplit = 40, objfun = deviance, verbose = TRUE)
> fmBH <- mob(medv ~ lstat + rm | zn + indus + chas +
+ nox + age + dis + rad + tax + crim + b + ptratio, data = BostonHousing,
+ control = .... [TRUNCATED]
-------------------------------------------
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
> plot(fmBH)
> coef(fmBH)
(Intercept) lstat rm
3 9.234880 -4.939096 0.6859136
6 3.963720 -2.766287 0.6881287
7 -1.798387 -0.267707 0.6538864
8 17.586490 -4.618975 0.3386744
9 68.297087 -16.354006 -0.1477939
> summary(fmBH, node = 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
> sctest(fmBH, node = 7)
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
> mean(residuals(fmBH)^2)
[1] 12.03518
> logLik(fmBH)
'log Lik.' -1310.506 (df=24)
> AIC(fmBH)
[1] 2669.013
> nt <- NROW(coef(fmBH))
> nk <- NCOL(coef(fmBH))
> data("PimaIndiansDiabetes2", package = "mlbench")
> PimaIndiansDiabetes <- na.omit(PimaIndiansDiabetes2[,
+ -c(4, 5)])
> fmPID <- mob(diabetes ~ glucose | pregnant + pressure +
+ mass + pedigree + age, data = PimaIndiansDiabetes, model = glinearModel,
+ famil .... [TRUNCATED]
> plot(fmPID)
Loading required package: vcd
> coef(fmPID)
(Intercept) glucose
2 -10.999447 0.06456780
4 -6.573067 0.04504490
5 -3.318569 0.02748038
> exp(coef(fmPID)[, 2])
2 4 5
1.066698 1.046075 1.027861
> risk <- round(100 * (exp(coef(fmPID)[, 2]) - 1), digits = 1)
*** Run successfully completed ***
> proc.time()
user system elapsed
3.548 0.080 3.636
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