如何使用qcc在EWMA控制图中绘制多个控制极限？

Question

我可以绘制一个3 sigma极限（nsigmas=3）的EWMA控制图。有人可以帮我在同一张图表上绘制其他控制线，例如1和2 sigma极限吗？

我能想到的唯一方法是使用每个限制创建单独的qcc对象，以某种方式提取它们的值，然后将它们绘制到EWMA图表上。当然有更简单的方法吗？

library(qcc)
LRR <- c(-0.1, -0.1, -0.09, -0.07, -0.27, -0.18,
-0.8, -0.86, -0.82,  0.01,  0.02)

q1 <- ewma(LRR, center =  -0.3, std.dev = 0.1 , lambda = 0.2,plot=F)

plot(q1, add.stats = F, label.limits = c("LCL", "UCL"), 
     xlab="Group", ylab= "LRR", ylim=c(-1.0,0.5),nsigmas = 3)

现在我想添加1和2 sigma控制限制。

谢谢。

Answer 1

一种解决方法是调整原始的plot.ewma.qcc功能，您可以找到here。 稍加努力，您就可以确定如何处理此功能中的限制。您可以创建自己的plot.ewma.qcc2函数，如下所示。 该函数很长，但已经过了一半，在注释add more control limits下，您将看到我添加了四个lines()函数调用，以计算和显示1和2 sigma控制行。

这是这样的：

plot.ewma.qcc2 <- function (x, add.stats = TRUE, chart.all = TRUE, label.limits = c("LCL", 
                                                                                    "UCL"), title, xlab, ylab, ylim, axes.las = 0, digits = getOption("digits"), 
                            restore.par = TRUE, ...) 
{
  object <- x
  if ((missing(object)) | (!inherits(object, "ewma.qcc"))) 
    stop("an object of class `ewma.qcc' is required")
  type <- object$type
  data.name <- object$data.name
  center <- object$center
  std.dev <- object$std.dev
  stats <- object$statistics
  limits <- object$limits
  newstats <- object$newstats
  newdata.name <- object$newdata.name
  violations <- object$violations
  nviolations <- length(violations)
  if (chart.all) {
    statistics <- c(stats, newstats)
    indices <- 1:length(statistics)
  }
  else {
    if (is.null(newstats)) {
      statistics <- stats
      indices <- 1:length(statistics)
    }
    else {
      statistics <- newstats
      indices <- seq(length(stats) + 1, length(stats) + 
                       length(newstats))
    }
  }
  if (missing(title)) {
    if (is.null(newstats)) 
      main.title <- paste("EWMA Chart\nfor", data.name)
    else if (chart.all) 
      main.title <- paste("EWMA Chart\nfor", data.name, 
                          "and", newdata.name)
    else main.title <- paste("EWMA Chart\nfor", newdata.name)
  }
  else main.title <- paste(title)
  oldpar <- par(no.readonly = TRUE)
  if (restore.par) 
    on.exit(par(oldpar))
  mar <- pmax(oldpar$mar, c(4.1, 4.1, 3.1, 2.1))
  par(bg = qcc.options("bg.margin"), cex = oldpar$cex * 
        qcc.options("cex"), mar = if (add.stats) 
          pmax(mar, c(7.6, 0, 0, 0))
      else mar)
  plot(indices, statistics, type = "n", ylim = if (!missing(ylim)) 
    ylim
    else range(statistics, limits), ylab = ifelse(missing(ylab), 
                                                  "Group Summary Statistics", ylab), xlab = ifelse(missing(xlab), 
                                                                                                   "Group", xlab), axes = FALSE)
  rect(par("usr")[1], par("usr")[3], par("usr")[2], 
       par("usr")[4], col = qcc.options("bg.figure"))
  axis(1, at = indices, las = axes.las, labels = if (is.null(names(statistics))) 
    as.character(indices)
    else names(statistics))
  axis(2, las = axes.las)
  box()
  top.line <- par("mar")[3] - length(capture.output(cat(main.title)))
  top.line <- top.line - if (chart.all & (!is.null(newstats))) 
    0.1
  else 0.5
  mtext(main.title, side = 3, line = top.line, font = par("font.main"), 
        cex = qcc.options("cex"), col = par("col.main"))
  abline(h = center, lty = 1)
  lines(indices, limits[indices, 1], lty = 2)
  lines(indices, limits[indices, 2], lty = 2)
  
# add more control limits
  
  lines(indices, center + object$sigma, lty = 2, col = "red")
  lines(indices, center - object$sigma, lty = 2, col = "red")
  
  lines(indices, center + 2*object$sigma, lty = 2, col = "green")
  lines(indices, center - 2*object$sigma, lty = 2, col = "green")
  
  points(indices, statistics, pch = 3, cex = 0.8)
  lines(indices, object$y[indices], type = "o", pch = 20)
  mtext(label.limits, side = 4, at = limits[nrow(limits), ], 
        las = 1, line = 0.1, col = gray(0.3), cex = par("cex"))
  if (nviolations > 0) {
    if (is.null(qcc.options("beyond.limits"))) 
      stop(".qcc.options$beyond.limits undefined. See help(qcc.options).")
    points(violations, object$y[violations], col = qcc.options("beyond.limits")$col, 
           pch = qcc.options("beyond.limits")$pch)
  }
  if (chart.all & !is.null(newstats)) {
    len.obj.stats <- length(stats)
    len.new.stats <- length(newstats)
    abline(v = len.obj.stats + 0.5, lty = 3)
    mtext("Calibration data", cex = par("cex") * 
            0.8, at = len.obj.stats/2, line = 0, adj = 0.5)
    mtext("New data", cex = par("cex") * 0.8, 
          at = len.obj.stats + len.new.stats/2, line = 0, adj = 0.5)
  }
  if (add.stats) {
    plt <- par()$plt
    usr <- par()$usr
    px <- diff(usr[1:2])/diff(plt[1:2])
    xfig <- c(usr[1] - px * plt[1], usr[2] + px * (1 - plt[2]))
    at.col <- xfig[1] + diff(xfig[1:2]) * c(0.15, 0.6)
    top.line <- 4.5
    mtext(paste("Number of groups = ", length(statistics), 
                sep = ""), side = 1, line = top.line, adj = 0, 
          at = at.col[1], font = qcc.options("font.stats"), 
          cex = par("cex") * qcc.options("cex.stats"))
    if (length(center) == 1) {
      mtext(paste("Center = ", signif(center[1], 
                                      digits = digits), sep = ""), side = 1, 
            line = top.line + 1, adj = 0, at = at.col[1], 
            font = qcc.options("font.stats"), cex = par("cex") * 
              qcc.options("cex.stats"))
    }
    else {
      mtext("Center is variable", side = 1, line = top.line + 
              1, adj = 0, at = at.col[1], font = qcc.options("font.stats"), 
            cex = par("cex") * qcc.options("cex.stats"))
    }
    mtext(paste("StdDev = ", signif(std.dev, digits = digits), 
                sep = ""), side = 1, line = top.line + 2, adj = 0, 
          at = at.col[1], font = qcc.options("font.stats"), 
          cex = par("cex") * qcc.options("cex.stats"))
    mtext(paste("Smoothing parameter = ", signif(object$lambda, 
                                                 digits = digits)), side = 1, line = top.line, adj = 0, 
          at = at.col[2], font = qcc.options("font.stats"), 
          cex = par("cex") * qcc.options("cex.stats"))
    mtext(paste("Control limits at ", object$nsigmas, 
                "*sigma", sep = ""), side = 1, line = top.line + 
            1, adj = 0, at = at.col[2], font = qcc.options("font.stats"), 
          cex = par("cex") * qcc.options("cex.stats"))
    mtext(paste("No. of points beyond limits =", nviolations), 
          side = 1, line = top.line + 2, adj = 0, at = at.col[2], 
          font = qcc.options("font.stats"), cex = par("cex") * 
            qcc.options("cex.stats"))
  }
  invisible()
}

Answer 2

非常感谢Paul。您的答案肯定比我的答案还要复杂！

我最终解决了这个问题；

“ escalc”找到LRR，然后

    rma(yi=LRR,vi=LRR_var)

est =来自此rma的“估计”

    q1 <- ewma(LRR, center =  est,  lambda = 0.2,labels=year,plot=F)
    LCL1 <- est - q1$sigma
    LCL2 <- est - 2*q1$sigma
    UCL1 <- est + q1$sigma
    UCL2 <- est + 2*q1$sigma
    LCL3 <- est - 3*q1$sigma
    UCL3 <- est + 3*q1$sigma

然后使用剧情

    abline(h=center,lty=1)
    lines(spline(1:4,LCL1,n=10), lty = "dotted", col = "grey")
    lines(spline(1:4,UCL1,n=10), lty = "dotted", col = "grey")
    lines(spline(1:4,LCL2,n=10), lty = "dotted", col = "black")
    lines(spline(1:4,UCL2,n=10), lty = "dotted", col = "black")
    lines(spline(1:4,LCL3,n=10), lty = "longdash", col = "black")
    lines(spline(1:4,UCL3,n=10), lty = "longdash", col = "black")