convergence.R

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convals <- function(x, ...) UseMethod('convals')
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# ---------------------------------------------------------------------------- #
convals.surrosurv <- function(x, ...) {
  models <- c('Clayton', 'Plackett', 'Hougaard', 'Poisson')
  models <-
    models[sapply(models, function(y)
      any(grepl(y, names(x))))]
  
  copulas <- function(cop) {
    f <- function() {
      res <- t(sapply(x[[cop]], function(y) {
        vals <- c(maxSgrad = tryCatch(
          max(abs(with(
            attributes(y$optimxRES), solve(hessian, grad)
          ))),
          error = function(x)
            return(Inf)
        ),
        minHev = tryCatch(
          min(eigen(attr(
            y$optimxRES, 'hessian'
          ))$values),
          error = function(x)
            return(-1)
        ),
        minREev = tryCatch(
          min(eigen(y$VarCor2)$values),
          error = function(x)
            return(-1)
        ))
        return(vals)
      }))
      rownames(res) <- paste(cop, rownames(res))
      return(res)
    }
    return(f)
  }
  Clayton = copulas('Clayton')
  Plackett = copulas('Plackett')
  Hougaard = copulas('Hougaard')
  Poisson = function() {
    which_models <- x[grepl('Poisson', names(x))]
    convres <- t(sapply(which_models,
                        function(y)
                          tryCatch({
                            vals <- c(maxSgrad = tryCatch(
                              max(abs(with(
                                y$optinfo$derivs, solve(Hessian, gradient)
                              ))),
                              error = function(x)
                                return(Inf)
                            ),
                            minHev = tryCatch(
                              min(eigen(y$optinfo$derivs$Hessian)$values),
                              error = function(x)
                                return(-1)
                            ),
                            minREev = tryCatch(
                              min(eigen(y$VarCor$trialref)$values),
                              error = function(x)
                                return(-1)
                            ))
                            return(vals)
                          }, error = function(x)
                            return(c(
                              Inf, -1, -1
                            )))))
    names(convres) <- names(which_models)
    return(convres)
  }
  
  fitRES <-
    do.call(rbind, lapply(models, function(x)
      eval(call(paste(
        x
      )))))
  fitRES[grepl('unadj|PoissonI', rownames(fitRES)), 'minREev'] <- NA
  class(fitRES) <- 'conv'
  return(fitRES)
}
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convergence <- function(x, kkttol = 1e-2, kkt2tol = 1e-8, ...)
  UseMethod('convergence')
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convergence.surrosurv <- function(x, kkttol = 1e-2, kkt2tol = 1e-8, ...) {
  ConvRES <- convals(x)
  checkConvRES <- cbind(ConvRES[, 1, drop = FALSE] <= kkttol,
                        ConvRES[, 2:3] > kkt2tol)
  
  class(checkConvRES) <- 'conv'
  return(checkConvRES)
}
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print.conv <- function(x, na.print = '---', ...) {
  class(x) <- 'matrix'
  print(x, na.print = na.print, ...)
}
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