outlierdc-class: "OutlierDC" class

In sooheang/OutlierDC: Outlier Detection for Censored Data

Description

The S4 class of OutlierDC

Objects from the "OutlierDC" Class

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

Slots

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:

data set after removing outliers

outlier.data:

data set containing outliers

coefficients:

estimated censored quantile regression coefficient matrix

fitted.mat:

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

score:

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

score.boot:

bootstrapping estimation for the outlying scores

boot.index:

estiamted bootstrap samples used for the outlying scores

boot.dist:

Empirical quantiles by the Jackknife-after-Bootstrap (JaB) estimation for outlying scores

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".

alg:

an outlier detection algorithm to be used

reg:

regression method such as Cox PH or censored quantile regression to be used

kr:

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

kb:

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

ks:

numeric value to be used for the tightness of upper fence cut-offs used for the scoring algorithm with update function

fence:

type of fence to be used in the model fitting

alpha:

numeric value of the significance

Methods

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.

See Also

OutlierDC-package
odc, coef, plot, show, update, JaB

Examples

    showClass("OutlierDC")

sooheang/OutlierDC documentation built on May 30, 2019, 6:31 a.m.