lkh.norm: Weighted Normal Likelihood for Independent Variables

In modello: Homemade Deep Learning Library

Description

Calculates the weighted Normal Likelihood for independent variables

lkh = ∑_i{w_i * ldnorm(y_i, μ_i, σ_i)}

Usage

lkh.norm(y, mu, s, w = NULL)

Arguments

y	observations, a reference object of class 'number'
mu	mean, a refernce object of class 'number'
s	standard deviation, a reference object of class 'number'
w	weights, a reference object of class 'number'

Value

Returns a reference object of class 'number'

Author(s)

Filippo Monari

Examples

modello.init(10, 10, 10, 10)
y = number(rnorm(10), dx=FALSE)
mu = number(rep(0, 10))
s = number(rep(1, 10))
w = number(runif(10))
lkh = lkh.norm(y, mu, s, w)
print(lkh)
print(lkh$v)
modello.close()

modello documentation built on Feb. 2, 2021, 9:06 a.m.