| dGaussian | R Documentation |
Get the density of a set of samples from a (multivariate) Gaussian distribution. For a random vector x, the density function is defined as:
sqrt(2 pi^p |Sigma|)^{-1} exp(-1/2 (x-mu )^T Sigma^{-1} (x-mu))
where p is the dimension of x.
dGaussian(x, mu, Sigma = NULL, A = NULL, LOG = TRUE)
x |
matrix, when x is a numeric vector, it will be converted to a matrix with 1 column! |
mu |
numeric, mean vector. |
Sigma |
matrix, covariance matrix, one of Sigma and A should be non-NULL. |
A |
matrix, the Cholesky decomposition of Sigma, an upper triangular matrix, one of Sigma and A should be non-NULL. |
LOG |
logical, return log density of LOG=TRUE, default TRUE. |
A numeric vector.
rGaussian
plot( dGaussian(x=seq(-5,5,length.out = 1000),mu = 0,Sigma = 1,LOG = FALSE) ,type = "l" )