Created
February 11, 2016 13:31
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Returns Multivariate Gaussian probability distribution for data points (rows) of X.
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| multGaussian = function(X) { | |
| #Number of rows | |
| m <- nrow(X) | |
| #Column means | |
| mu <- colMeans(X) | |
| #Number of columns | |
| k = length(mu) | |
| #Substruct column means from data points (center data to 0) | |
| X_centered <- X - matrix(1, m, 1) %*% matrix(mu, 1, k) | |
| #Compute sum of averaged squared values - variances of columns | |
| sigma2 <- colSums(as.matrix(X_centered) ^ 2) / m | |
| #Make a diagonal variance matrix | |
| sigma2 = diag(sigma2) | |
| #Compute p. Multivariate Gaussian probability Distribution for rows of X | |
| p = (2*pi)^(-k/2) * det(sigma2)^(-1/2) * exp((-1/2) * rowSums(X_centered %*% solve(sigma2) * X_centered)) | |
| return(p) | |
| } |
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