dobin | R Documentation |
This function computes a set of basis vectors suitable for outlier detection.
dobin(xx, frac = 0.95, norm = 1, k = NULL)
xx |
The input data in a dataframe, matrix or tibble format. |
frac |
The cut-off quantile for |
norm |
The normalization technique. Default is Min-Max, which normalizes each column to values between 0 and 1. |
k |
Parameter |
A list with the following components:
|
The basis vectors suitable for outlier detection. |
|
The dobin coordinates of the data |
|
The The associated |
|
The pairs in |
|
Columns in |
# A bimodal distribution in six dimensions, with 5 outliers in the middle. set.seed(1) x2 <- rnorm(405) x3 <- rnorm(405) x4 <- rnorm(405) x5 <- rnorm(405) x6 <- rnorm(405) x1_1 <- rnorm(mean = 5, 400) mu2 <- 0 x1_2 <- rnorm(5, mean=mu2, sd=0.2) x1 <- c(x1_1, x1_2) X1 <- cbind(x1,x2,x3,x4,x5,x6) X2 <- cbind(-1*x1_1,x2[1:400],x3[1:400],x4[1:400],x5[1:400],x6[1:400]) X <- rbind(X1, X2) labs <- c(rep(0,400), rep(1,5), rep(0,400)) dob <- dobin(X) autoplot(dob)
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