Update class means

Usage

update_b(beta, Omega, z, m, Sigma_b_0_inv, mu_b_0)

Arguments

beta: [matrix(nrow = P_r, ncol = N)]
The matrix of the decider-specific coefficient vectors.
Omega: [matrix(nrow = P_r * P_r, ncol = C)]
The matrix of vectorized class covariance matrices as columns.
z: [numeric(N)]
The decider class allocations.
m: [numeric(C)]
The vector of current class frequencies.
Sigma_b_0_inv: [matrix(P_r, P_r)]
The prior precision of the class mean.
mu_b_0: [numeric(P_r)]
The mean vector of the normal prior for each b_c.

Value

A matrix of updated means for each class in columns.

Examples

N <- 100
b <- cbind(c(0, 0), c(1, 1))
Omega <- matrix(c(1, 0.3, 0.3, 0.5, 1, -0.3, -0.3, 0.8), ncol = 2)
z <- c(rep(1, N / 2), rep(2, N / 2))
m <- as.numeric(table(z))
beta <- sapply(
  z, function(z) oeli::rmvnorm(n = 1, b[, z], matrix(Omega[, z], 2, 2))
)
update_b(
  beta = beta, Omega = Omega, z = z, m = m,
  Sigma_b_0_inv = diag(2), mu_b_0 = c(0, 0)
)
#>            [,1]     [,2]
#> [1,]  0.0401460 1.125959
#> [2,] -0.1740866 1.032935