R/internal.funs.r

In nshi-stat/netiim3: Improved Inference Methods for Network Meta-Analysis

vmat <- function(q2, p){

  i1 <- 1; i2 <- p

  Sg <- matrix(numeric(p*p), p, p)

  for(i in 1:p){

    Sg[i,(i:p)] <- q2[i1:i2]

    i1 <- i2 + 1
    i2 <- i2 + p - i

  }

  Sg <- Sg + t(Sg); diag(Sg) <- diag(Sg)/2

  return(Sg)

}

cmat <- function(q2, p){

  Sg <- q2*diag(p)

  return(Sg)

}

pmat <- function(Si, wi){

  pl <- length(wi)

  R <- matrix(numeric(pl*pl), pl)

  for(i in 1:pl){
    for(j in 1:pl){

      R[i,j] <- Si[wi[i], wi[j]]

    }
  }

  return(R)

}

imat <- function(Si, wi, p){

  pl <- length(wi)

  R <- matrix(numeric(p*p), p)

  for(i in 1:pl){
    for(j in 1:pl){

      R[wi[i], wi[j]] <- Si[i, j]

    }
  }

  return(R)

}

ivec <- function(yi, wi, p){

  pl <- length(wi)

  R <- numeric(p)

  for(i in 1:pl) R[wi[i]] <- yi[i]

  return(R)

}

ivec2 <- function(yi, wi, p){

  pl <- length(wi)

  R <- rep(NA,times = p)

  for(i in 1:pl) R[wi[i]] <- yi[i]

  return(R)

}

gmat <- function(g1, g2, p){

  G <- diag(0, p) + g2
  diag(G) <- g1
  return(G)

}