EvaluationList-class {distrTEst} | R Documentation |

## Class "EvaluationList"

### Description

Several objects of class "Evaluation" may be gathered in a list of class "EvaluationList", if they all have the same result-format and also share the same data-set.

### Objects from the Class

Objects may be created by the generating function `EvaluationList`

, i.e.;
`EvaluationList(..., name0 = "a list of \"Evaluation\" objects")`

, where all arguments passed through ...
have to be objects of class "Evaluation", the corresponding result-slots have to contain
data.frames of identical dimension; the corresponding calls have to have identical `object`

-arguments
(for the data set), and the corresponding `Data`

-slots have to be identical.

### Slots

`name`

:Object of class

`"character"`

: the name of the EvaluationList object`Elist`

:Object of class

`"list"`

: the list of Evaluation objects

### Accesor/Replacement methods

- Elist
`signature(object = "EvaluationList")`

: returns the list with the Evaluation objects- name
`signature(object = "EvaluationList")`

: returns/modifies the name of the EvaluationList object

### Methods

- Data
`signature(object = "EvaluationList")`

: returns the common`Data`

-slot of one of the Evaluation objects- plot
`signature(object = "EvaluationList")`

: returns grouped boxplots of the results`signature(object = "EvaluationList")`

: for each list element returns the name of the data object, its filename, the estimator used and the result- show
`signature(object = "EvaluationList")`

: as print- summary
`signature(object = "EvaluationList")`

: returns the name of the data object, its filename, the estimator used and a statistical summary of the result

### Author(s)

Thomas Stabla statho3@web.de,

Florian Camphausen fcampi@gmx.de,

Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,

Matthias Kohl Matthias.Kohl@stamats.de

### See Also

`Dataclass-class`

`Simulation-class`

`Contsimulation-class`

`Evaluation-class`

`print-methods`

`plot-methods`

`simulate-methods`

`summary-methods`

### Examples

```
N <- Norm() # N is a standard normal distribution.
C <- Cauchy() # C is a Cauchy distribution
cs <- Contsimulation(filename = "csim",
runs = 15,
samplesize=500,
seed=setRNG(),
distribution.id = N,
distribution.c = C,
rate = 0.1)
simulate(cs)
# Each of the 25000 random numbers is ideal (N-distributed) with
# probability 0.9 and contaminated (C-distributed) with probability = 0.1
summary(cs)
ev1 <- evaluate(cs, mean) # estimates the data with mean
ev1 # bad results
ev2 <- evaluate(cs,median) # estimates the data with median
ev2 # better results because median is robust
savedata(ev1)
# saves the EvaluationList with result as "csim.mean" and without result as
# "csim.mean.comment" in the working directory # of R - "csim" is the
# filename of the Contsimulation object, mean the name of the estimator
rm(ev1)
cload("csim.mean")
# loads the EvaluationList without result - the object is called ev1.comment
ev1.comment
load("csim.mean") # loads the EvaluationList with result
ev1
ElistObj <- EvaluationList(ev1,ev2,name0="myEvalList")
plot(ElistObj,ylim=matrix(c(-0.5,0.5,0.5,4),nrow=2),main=c("location","scale"))
plot(ElistObj,ylim=c(-0.5,0.5),main=c("location"),runs0=3:12,dims0=1,evals0=2)
ElistObj
summary(ElistObj)
#clean up
unlink("csim.mean")
unlink("csim.mean.comment")
```

*distrTEst*version 2.8.2 Index]