R/print.sumry.glm.R

In DAAG: Data Analysis and Graphics Data and Functions

print.sumry.glm <-
function (x, digits = max(3L, getOption("digits") - 3L), symbolic.cor = FALSE, 
          signif.stars = getOption("show.signif.stars"), call=FALSE, deviance.residuals=FALSE, 
          show.iter=10, ...) 
{
  if(is.null(digits))digits <- max(3L, getOption("digits") - 3L)
  if(call)cat("\nCall:\n", paste(deparse(x$call), sep = "\n", collapse = "\n"), 
      "\n\n", sep = "")
  if(deviance.residuals){cat("Deviance Residuals: \n")
  if (x$df.residual > 5) {
    x$deviance.resid <- setNames(quantile(x$deviance.resid, 
                                          na.rm = TRUE), c("Min", "1Q", "Median", "3Q", "Max"))
  }
  xx <- zapsmall(x$deviance.resid, digits + 1L)
  print.default(xx, digits = digits, na.print = "", print.gap = 2L)
  cat('\n')
  }
  if (length(x$aliased) == 0L) {
    cat("\nNo Coefficients\n")
  }
  else {
    df <- if ("df" %in% names(x)) 
      x[["df"]]
    else NULL
    if (!is.null(df) && (nsingular <- df[3L] - df[1L])) 
      cat("Coefficients: (", nsingular, " not defined because of singularities)\n", 
          sep = "")
    else cat("Coefficients:\n")
    coefs <- x$coefficients
    if (!is.null(aliased <- x$aliased) && any(aliased)) {
      cn <- names(aliased)
      coefs <- matrix(NA, length(aliased), 4L, dimnames = list(cn, 
                                                               colnames(coefs)))
      coefs[!aliased, ] <- x$coefficients
    }
    printCoefmat(coefs, digits = digits, signif.stars = signif.stars, 
                 na.print = "NA", ...)
  }
  cat("\n(Dispersion parameter for ", x$family$family, " family taken to be ", 
      format(x$dispersion), ")\n\n", apply(cbind(paste(format(c("Null", 
                                                                "Residual"), justify = "right"), "deviance:"), format(unlist(x[c("null.deviance", 
                                                                                                                                 "deviance")]), digits = max(5L, digits + 1L)), " on", 
                                                 format(unlist(x[c("df.null", "df.residual")])), " degrees of freedom\n"), 
                                           1L, paste, collapse = " "), sep = "")
  if (nzchar(mess <- naprint(x$na.action))) 
    cat("  (", mess, ")\n", sep = "")
  if(is.null(show.iter)|x$iter>show.iter)
  cat("AIC: ", format(x$aic, digits = max(4L, digits + 1L)), 
      "\n\n", "Number of Fisher Scoring iterations: ", x$iter, 
      "\n", sep = "")
  correl <- x$correlation
  if (!is.null(correl)) {
    p <- NCOL(correl)
    if (p > 1) {
      cat("\nCorrelation of Coefficients:\n")
      if (is.logical(symbolic.cor) && symbolic.cor) {
        print(symnum(correl, abbr.colnames = NULL))
      }
      else {
        correl <- format(round(correl, 2L), nsmall = 2L, 
                         digits = digits)
        correl[!lower.tri(correl)] <- ""
        print(correl[-1, -p, drop = FALSE], quote = FALSE)
      }
    }
  }
  cat("\n")
  invisible(x)
}