mahalanobis_distance {OutliersLearn}

mahalanobis_distance

Description

Calculates the mahalanobis_distance given the input data

Usage

mahalanobis_distance(value, sample_mean, sample_covariance_matrix)

Arguments

value

Point to calculate the mahalanobis_distance

sample_mean

Sample mean

sample_covariance_matrix

Sample Covariance Matrix

Value

Mahalanobis distance associated to the point

Author(s)

Andres Missiego Manjon

Examples

inputData = t(matrix(c(3,2,3.5,12,4.7,4.1,5.2,
4.9,7.1,6.1,6.2,5.2,14,5.3),2,7,dimnames=list(c("r","d"))));
inputData = data.frame(inputData);
inputData = as.matrix(inputData);
sampleMeans = c();
for(i in 1:ncol(inputData)){
  column = inputData[,i];
  calculatedMean = sum(column)/length(column);
  print(sprintf("Calculated mean for column %d: %f", i, calculatedMean))
  sampleMeans = c(sampleMeans, calculatedMean);
}
covariance_matrix = cov(inputData);
distance = mahalanobis_distance(inputData[3,], sampleMeans, covariance_matrix);