maxlof {dprep} | R Documentation

## Detection of multivariate outliers using the LOF algorithm

### Description

A function that detects multivariate outliers using the local outlier factor for a matrix over a range of neighbors called Minpts.

### Usage

    maxlof(data, name = "", minptsl = 10, minptsu = 20)

### Arguments

`data` | dataset for outlier detection
`name` | name to be given to the dataset, used in the graph title.
`minptsl` | lower bound for the range of number of neighbors
`minptsu` | upper bound for the range of number of neighbors

### Details

Calls on the function "lofactor" to compute the local outlier factor for each number of neighbors in the range [minptsl, minptsu]. Also displays a plot of the factors for each observation of the dataset. In the plot, the user should seek to identify observations with large gaps between outlyingness measures. These would be the candidate for outliers.

### Value

`maxlofactor` | a vector containing the index of each observation of the dataset and the corresponding local outlier factor.

### Author(s)

Caroline Rodriguez

### References

Breuning, M., Kriegel, H., Ng, R.T, and Sander. J. (2000). LOF: Identifying density-based local outliers. In Proceedings of the ACM SIGMOD International Conference on Management of Data.

### Examples

    #Detecting top 10 outliers in Breastw-class1 using the LOF algorithm
    data(breastw)
    breastw1.lof=maxlof(breastw[breastw[,10]==1,],name="",30,40)
    breastw1.lof[order(breastw1.lof,decreasing=TRUE)][1:10]

[Package dprep version 1.0 Index]