R/svfit.R

In Hariharasubramanyam/metricsComplete:

  svfit <- function (y, omega, P) {
    N <- length(y)
    alpha_up_init <- rnorm(P, 0, 1)
    alpha_wt_init <- rep(1, P)/P
    eta_sim <- matrix(rnorm(P * N, 0, 1), P, N)
    u_sim <- matrix(runif(P * N, 0, 1), P, N)
    
    for (i in 1:N) {
      u_sim[, i] <- sort(u_sim[, i])
    }
    lb <- rep(0, length(omega)) + 0.01
    ub <- rep(1, length(omega)) - (2 * (10^-10))
    omega = c(var(y) * (1 - 0.95), 0.95, 0.1)
    
    sv_proxy <- function(par) {
      output <- svll(par, y, eta_sim, u_sim, alpha_up_init, 
                          alpha_wt_init)
      return(output)
    }
    trial <- optim(par = omega, fn = sv_proxy, upper = ub, lower = lb, control = list(trace = 1), method = "L-BFGS-B", hessian = T)
    trial$value <- -trial$value
    return(trial)
  }