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Last data update: 2014.03.03

R: Prediction from bagged Discrete-Time Survival Trees

predict.DStreebag

R Documentation

Prediction from bagged Discrete-Time Survival Trees

Description

Predict the median survival time, hazard and survival probabilities from a DStreebag object.

Usage

## S3 method for class 'DStreebag'
predict(object, data, ...)

Arguments

`object`	a fitted object of class `DStreebag`
`data`	data frame containing the values at which predictions are required. The predictors referred to in the right side of `formula(object)` as well as the 'status' variable must be present by name in `newdata`.
`...`	further arguments passed to or from other methods.

Value

A named list with the following elements: The vector MedSurv contains the predicted median survival times of the observations in data. The matrices Surv and Haz contain the predicted probabilities and hazard rates, respectively, where each row refers to an individual and each column refers to an observed time point (1,2,...).

References

Bou-Hamad I., Larocque D.,Ben-Ameur H., Masse L. C., Vitaro F. and Tremblay R. E. (2009), Discrete-Time Survival Trees. Canadian Journal of Statistics 37 (1), 17-32.

Hothorn T., Lausen B., Benner A. and Radespiel-Troeger M. (2004), Bagging Survival Trees. Statistics in Medicine 23 (1), 77-91.

Examples

data(cost)
## Discretize observed days to years
d.cost<-dis.cost(cost)

# Bagging Tree
bag <- bag(time~prevStroke+age+sex+alcohol+smoke,status="status",data=d.cost[1:330,],nBoot=10)
pred <- predict(bag,newdata=d.cost[331:518,])
pred$MedSurv

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(DStree)
Loading required package: rpart
Loading required package: pec
Loading required package: prodlim
Loading required package: Ecdat
Loading required package: Ecfun

Attaching package: 'Ecfun'

The following object is masked from 'package:base':

    sign


Attaching package: 'Ecdat'

The following object is masked from 'package:datasets':

    Orange

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DStree/predict.DStreebag.Rd_%03d_medium.png", width=480, height=480)
> ### Name: predict.DStreebag
> ### Title: Prediction from bagged Discrete-Time Survival Trees
> ### Aliases: predict.DStreebag
> 
> ### ** Examples
> 
> data(cost)
> ## Discretize observed days to years
> d.cost<-dis.cost(cost)
> 
> # Bagging Tree
> bag <- bag(time~prevStroke+age+sex+alcohol+smoke,status="status",data=d.cost[1:330,],nBoot=10)
> pred <- predict(bag,newdata=d.cost[331:518,])
> pred$MedSurv
  408   233   541   578   301   556   222   403    93   404    80    32   597 
   NA  2.96    NA  3.11  2.70    NA    NA  3.18  3.71    NA  3.86    NA    NA 
  432   338   567   355   135   299   513   463   596   384   503    39    84 
   NA  3.62    NA    NA  2.41    NA    NA    NA    NA    NA  3.31  3.08    NA 
596.1   419   240   176   421   422   572   502   203   585   455    77    28 
   NA  4.28    NA  3.39  3.27  3.46  2.79  3.50  3.69    NA    NA  2.56  3.60 
  281   117   245   120   481 408.1   354   407   383 135.1    86   115   275 
   NA    NA    NA    NA    NA    NA    NA  3.24  3.79  2.75    NA  3.11    NA 
  576    43   223   215   506   344   472    23 407.1    87   269   509 117.1 
 3.47    NA  3.47  3.88  2.95  4.25    NA  3.69  4.00    NA  4.14    NA  3.54 
  436   268   490   305 576.1   584    19   263 506.1   593   118   282   258 
 2.90    NA  2.89  3.20  3.48    NA  3.70    NA    NA    NA    NA    NA    NA 
593.1   378 215.1    22   248   603   400   545    26   289   357   560   445 
   NA    NA    NA    NA  2.99  4.85    NA  3.31    NA    NA    NA    NA    NA 
  246   255 384.1   373   381 403.1   486    81 597.1  80.1    98   304 246.1 
 3.87  2.93    NA  2.92  3.74  4.28  3.79  3.00    NA    NA  3.48    NA    NA 
233.1    65    67    15 556.1   318 432.1    24 403.2    44   483   461   629 
 3.35    NA  3.59    NA    NA    NA  2.87    NA    NA  3.90    NA    NA  3.49 
  256   577   580   510   459    48   123 263.1    13   595   569   346    72 
   NA  3.14  3.66  3.07  3.87    NA    NA    NA  3.27  3.42    NA  2.46  3.40 
  312   153   173    33   229 545.1   476  23.1 215.2   259  43.1   371 577.1 
 3.17  3.84    NA  4.09  3.36    NA  3.79    NA    NA    NA    NA  2.74  3.60 
  104 259.1   561  43.2   351   423   146   113  26.1   606   390   361 481.1 
 3.63  2.67    NA  3.38  3.59  2.01    NA    NA    NA    NA  3.58    NA    NA 
 43.3  13.1   175   380 556.2   194 486.1  43.4    35 240.1   253   227    82 
   NA  4.10  4.09    NA    NA  3.92    NA  2.82    NA    NA    NA    NA    NA 
  516    78   558    69  35.1 351.1   200    11 246.2  13.2 304.1 576.2   429 
   NA    NA    NA  3.67  3.08  3.07  3.12    NA    NA  4.04  3.36  2.12    NA 
  607   286   565 597.2   446 305.1   435 481.2   388    25   295 565.1   591 
   NA    NA    NA    NA  4.86  2.56  2.70  3.85    NA  3.64    NA    NA    NA 
 67.1 597.3    89  72.1   285 268.1 354.1    62 567.1 463.1  69.1   241  65.1 
 4.58    NA  3.29    NA    NA    NA    NA    NA  4.01  2.61    NA  4.95    NA 
  352 558.1 344.1     5 378.1   573    75    83   613 423.1   307  81.1 229.1 
 3.69    NA    NA  3.76    NA    NA  3.78  2.77  2.77  3.62  3.86  3.08  3.09 
 72.2  77.1   205  23.2    49   624 118.1 403.3 503.1 624.1   583 445.1 223.1 
 4.27    NA    NA  3.97  3.66    NA    NA    NA  3.98  4.09    NA    NA  3.97 
  142 258.1 556.3   163   147   290 205.1 503.2 556.4 472.1 388.1 255.1   612 
 4.83  2.87    NA  3.30  4.18    NA    NA  3.48    NA    NA    NA  4.09  3.09 
565.2   162 120.1  98.1 378.2   193 176.1 142.1   168   121   550 163.1   547 
   NA  2.50  3.29    NA    NA    NA    NA    NA  3.87    NA    NA    NA  2.67 
290.1 304.2   291   234   571   277 258.2   610   358 584.1 603.1 490.1 223.2 
 3.19  4.58  3.17  3.53    NA  2.58  2.95    NA  3.26  3.50  2.70  3.19  3.77 
407.2   247   487 234.1   322    92  32.1   474  32.2 168.1 404.1 281.1 269.1 
 4.31    NA  3.29  3.53  4.54  2.85    NA  3.32    NA  3.69  3.23  3.20    NA 
  471    38 120.2 245.1 595.1  35.2   164   148    41 281.2    51    57 560.1 
 3.07    NA    NA  3.57    NA  3.38  3.90    NA    NA    NA    NA    NA  2.90 
490.2    55 253.1   599 612.1 123.1   496   575 576.3 162.1 281.3   143 163.2 
 3.17    NA  3.59    NA  2.62    NA  3.78  2.36    NA    NA  3.41    NA  3.69 
234.2 481.3     3   284   347 168.2 575.1 513.1   328  62.1 290.2   345 593.2 
 3.99    NA  4.03    NA    NA  4.06    NA    NA  2.46    NA  3.96    NA    NA 
318.1 513.2 513.3  51.1    40 
   NA    NA  3.89    NA    NA 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>