R cmd检查中的警告

在执行R cmd检查时，我收到以下警告：

正在检查S3泛型/方法一致性。。。警告

绘图： 函数（x，…）

plot.logReg： 函数（对象、cv、变量名等） 请参阅“编写R扩展”手册中的“通用函数和方法”一节

我真的很难找到这个问题的根源。我将在下面发布我的代码

谢谢你的时间和帮助

plot.logReg <- function(object, cv, varName, ...) {
  keep_loop = TRUE
  while (keep_loop) {
    switch (menu(c("QQ plot for residuals of logistic regression",
                   "Outlier Detection",
                   "Logistic regression model fit", "exit"),
                 title = "Which plot?"),
            1 == {
              qqnorm(object$residuals,
                     main = "Normal QQ-Plot of Model Residuals",
                     ylab = "Residuals")
              # plot residuals against the theoretical quantils of
              # the standard normal distribution and give the plot the titel
              # "Normal QQ-Plot of Model Residuals"
              qqline(object$residuals)
              # add the line through the origin
            },
            2 == {
              mydata2 <- cbind(object$data, c(1:length(object$y)))
              #create a new column with the index values
              colnames(mydata2)[ncol(mydata2)] <- "Index"
              # name the new column Index
              plot(mydata2$Index, object$pearsonStandard, xlab = "Index",
                   ylab = "standardized Pearson Residuals",
                   main = "Outlier Detection")
              # plot the values of Index against the standardized Pearson
              #residuals
              abline(h = cv, lty = 2)
              abline(h = -cv, lty = 2)
              # creates two horizontal lines in dependence of the critical
              # value cv
              textxy(as.numeric(names(
                object$pearsonStandard[which(object$pearsonStandard <- cv |
                                               object$pearsonStandard > cv)])),
                object$pearsonStandard[which(object$pearsonStandard <- cv |
                                               object$pearsonStandard > cv)],
                as.numeric(names(object$pearsonStandard[
                  which(object$pearsonStandard <- cv |
                          object$pearsonStandard > cv)])),
                cex = 0.7,offset = -1)
              # applies the index number to those values, that are ourtside of
              # the interval [-cv; cv]
            },
            3 == {
              mydata2 <- object$data[with(object$data,
                                          order(object$data %>%
                                                  pull(varName))), ]
              # creates a new data frame with ordered data
              # only the desired variable is ordered from small to big values
              # after ordering the observations are still the same but ordererd
              # according to the variable varName
              points <- (predict.logReg(logReg(object$y ~ varName, data =
                                                 mydata2)))
              # claculates points of the predictions given the values of varName
              plot(mydata2 %>% pull(varName), points[, 1],
                   xlab = "varName", ylab = "Probabilities")
              # plotting varName against their predictions
              lines(x = mydata2 %>% pull(varName), y = points[, 1])
              # draws a line through the predictions
            },
            4 == {
              keep_loop = FALSE
              # stops the loop
            })
  }
}

plot.logReg