modello (version 0.1.1)

ldmvnorm: Multivariante Normal: log-density

Description

Considering a Multivariate Normal Distribution calculates the log-density $$ld = -0.5 * (n * log(2 * \pi) * log(|\Sigma|) + y^T \Sigma y)$$

Usage

ldmvnorm(y, mu, E)

Arguments

y

observations, numeric or reference object of class 'number'

mu

mean vector, numeric of reference object of class 'number'

E

covariance matrix, numeric of reference object of class 'number'

Value

Returns a 'numeric' or a reference object of class 'number'

Examples

# NOT RUN {
modello.init(10, 10, 10, 10)
y = number(rnorm(10))
mu = number(rep(0, 10))
E = number(diag(1, 10))
ld = ldmvnorm(y, mu, E)
print(ld)
print(ld$v)
modello.close()
# }