mexi: ME-XI For First Moment

In JoaoPedro2536/univ.em:

Description

Find the first moment of the truncated multivariate normal distributions for the rectangles which will be used to calculate the estimate of the covariance matrix.

Usage

mexi(data, mu, sigma)

Arguments

data	Data in the form of multivariate grouped data.
mu	Mean vector.
sigma	Covariance matrix

Value

Returns a matrix with the references of the first moments.

Examples

library(MASS)
library(em.univ)
library(tmvtnorm)

simulateddata = em.univ::mult_simul(mm = c(68,68),
                          ss = base::matrix(c(3,2,2,6),2,2) ,
                          n_data_sets = 1,
                          breaks_x = c(-Inf,64,65,66,67,68,69,70,71,72,Inf),
                          breaks_y = c(-Inf,64.2,65.2,66.2,
                                       67.2,68.2,69.2,70.2,
                                       71.2,72.2,Inf),
                          lower_x = base::rep(c(-Inf,64,65,66,67,
                                          68,69,70,71,72),10),
                          lower_y = c(base::rep(-Inf,10),
                                      base::rep(64.2,10),
                                      base::rep(65.2,10),
                                      base::rep(66.2,10),
                                      base::rep(67.2,10),
                                      base::rep(68.2,10),
                                      base::rep(69.2,10),
                                      base::rep(70.2,10),
                                      base::rep(71.2,10),
                                      base::rep(72.2,10)),
                          upper_x = base::rep(c(64,65,66,67,68,69,70,
                                                71,72,Inf),10),
                          upper_y = c(base::rep(64.2,10),
                                      base::rep(65.2,10),
                                      base::rep(66.2,10),
                                      base::rep(67.2,10),
                                      base::rep(68.2,10),
                                      base::rep(69.2,10),
                                      base::rep(70.2,10),
                                      base::rep(71.2,10),
                                      base::rep(72,2,10),
                                      base::rep(Inf,10))
)



mu2<- c(67,67)
sigma2<- base::matrix(c(3.1,2.2,2.2,4.3),2,2)


out<- em.univ::mexi(data = simulateddata[,,1],
           mu = mu2,
           sigma = sigma2)


out

JoaoPedro2536/univ.em documentation built on Dec. 18, 2021, 1:38 a.m.