This is an grid based anomaly detection algorithm, which suitable for large dataset.
Reference Paper: Grid Based Outlier Detection in Large Data Sets for Combine Harvester Author: Ying Gu, Conference: IEEE-INDIN 2017(IEEE 15th International Conference on Industrial Informatics)
The installation need the devtools
package: https://github.com/hadley/devtools
library("devtools")
install_github("blatoo/r_gbod")
Details in file "gbod_usage.html" Input data is a dataframe without missing values
library(dplyr)
library(gbod)
df = na.omit(read.csv(...)) # input dataframe
# use the basic method
res = gbod(df, n_partition=10, outlier_percent=1)
# use the scored method
res = gbod_score(df, partition_range = c(5,8), outlier_percent=1)