Description Objects from the Class Slots Methods See Also Examples

The `OutlierDC`

class presents outlier detection algorithms for censored data.

Objects can be created by calls of the form `new("OutlierDC")`

.

`call`

:evaluated function call

`formula`

:formula to be used with the type of

`"Formula"`

`raw.data`

:data to be used with the type of

`"data.frame"`

`refined.data`

:the data set after removing outliers

`outlier.data`

:the data set containing outliers

`coefficients`

:the estimated censored quantile regression coefficient matrix

`fitted.mat`

:the censored quantile regression fitted value matrix with the type of

`"matrix"`

`score`

:outlying scores (scoring algorithm) or residuals (residual-based algorithm)

`cutoff`

:estimated scale parameter for the residual-based algorithm

`lower`

:lower fence vector used for the boxplot and scoring algorithms with the type of

`"vector"`

`upper`

:upper fence vector used for the boxplot and scoring algorithms with the type of

`"vector"`

`outliers`

:logical vector to determine which observations are outliers

`n.outliers`

:number of outliers to be used. The object of class

`"integer"`

.`method`

:outlier detection method to be used

`rq.model`

:censored quantile regression to be fitted

`k_r`

:a value to be used for the tightness of cut-offs in the residual-based algorithm

`k_b`

:a value to be used for the tightness of cut-offs in the boxplot algorithm

`bound`

:type of fence to be used in the model fittind

`k_s`

:a value to be used for the tightness of upper fence cut-offs used for the scoring algorithm with

`update`

function

- coef
`signature(object = "OutlierDC")`

: Print the coefficient matrix of censored quantile regression to be used. See`coef`

.- plot
`signature(x = "OutlierDC", y = "missing")`

: See`plot`

.- show
`signature(object = "OutlierDC")`

: See`show`

.- update
`signature(object = "OutlierDC")`

: Update the fitted object to find outliers in scoring algorithm. See`update`

.

`OutlierDC-package`

`coef`

, `plot`

, `show`

, `update`

1 | ```
showClass("OutlierDC")
``` |

```
Loading required package: survival
Loading required package: quantreg
Loading required package: SparseM
Attaching package: 'SparseM'
The following object is masked from 'package:base':
backsolve
Attaching package: 'quantreg'
The following object is masked from 'package:survival':
untangle.specials
Loading required package: Formula
Package OutlierDC (0.3-0) loaded.
Class "OutlierDC" [package "OutlierDC"]
Slots:
Name: call formula raw.data refined.data outlier.data
Class: language Formula data.frame data.frame data.frame
Name: coefficients fitted.mat score cutoff lower
Class: data.frame matrix vector vector vector
Name: upper outliers n.outliers method rq.model
Class: vector vector integer character character
Name: k_r k_b bound k_s
Class: numeric numeric character numeric
```

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